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Spring 2020 - Applied Learning Practicum (INTR-799-06) - Full TermPamela SmithMore info
Spring 2020 - Data Science & Big Data Analy (ITS-836-52) - Full TermMultiple Instructors More info
Spring 2020 - Infer Stats in Decision-Making (DSRT-734-05) - Second Bi-TermMultiple Instructors
Fall 2019 - Applied Learning Practicum (INTR-799-03) - Full TermPamela SmithMore info
Fall 2019 - InfoTech Import in Strat Plan (ITS-831-05) - First Bi-TermMultiple Instructors More info
Spring 2020 - Data Science & Big Data Analy (ITS-836-52) - Full Term
InformationSpring 2020 - Data Science & Big Data Analy (ITS-836-52) - Full Term
Information
Big Data Analytics
iden�fy fundamental concepts of Big Data management
and analy�cs.
become competent in recognizing challenges faced by
applica�ons dealing with very large volumes of data as
well as in proposing scalable solu�ons for them.
be able to understand how Big Data impacts business
intelligence, scien�fic discovery, and our day-to-day life.
Course Descrip�on: In this course the students explore key data analysis and management
techniques, which applied to massive datasets are the cornerstone
that enables real-�me decision making in distributed environments,
business intelligence in the Web, and scien�fic discovery at large
scale. In par�cular, students examine the map-reduce parallel
compu�ng paradigm and associated technologies such as distributed
file systems, no-sql databases, and stream compu�ng engines. This
highly interac�ve course is based on the problem-based learning
philosophy. Students are expected to make use of technologies to
design highly scalable systems that can process and analyze Big Data
for a variety of scien�fic, social, and environmental challenges.
Course
Objec�ves/Learner
Outcomes:
Course Objec�ves/Learner Outcomes:
Upon comple�on of this course, the student will:
Prerequisites: There are no prerequisites for this course.
Books and
Resources:
Required Text
EMC Educa�on Service (Eds). (2015) Data Science and Big Data Analytics:
Discovering, Analyzing, Visualizing, and Presenting Data, Indianapolis,
IN: John Wiley & Sons, Inc
××
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https://ucumberlands.blackboard.com/webapps/blackboard/execute/courseMain?course_id=_114565_1
CSCI 561
Article Review Instructions
After reading through your assignments this week, you are to pick a topic of interest that was mentioned in the reading assignment. Using the Jerry Falwell Library and other scholarly resources, you are to locate a peer reviewed journal related to the topic of your interest. Read the journal article thoroughly so you can discuss it. If you wish to use something other than a peer reviewed journal, please consult with your instructor before starting the assignment.
You will then prepare an article review ...
Agg PlansThe owner of a small mill-working plant that builds cabin.docxnettletondevon
Agg PlansThe owner of a small mill-working plant that builds cabinets is developing his aggregate plan for the next year. The relevant cost data and forecast for the next 4 quarters is provided below. The company currently has 12 employees and works one 8 hour shift each day with 2 paid 15 minute breaks. Assume each quarter has 65 working days, and that it currently has no units in stock. Use this information and the information from the table to answer the questions below. CostsForecastOther DataHolding Cost/Unit/Quarter$25.00Qtr 11500Labor Hours/Unit4.5Hiring Cost$2,500.00Qtr 21200Beginning Inventory0Layoff Cost$3,500.00Qtr 32100Subcontract Cost$135.00Qtr 41650Avg. Labor Cost/Hour$18.00Overtime Labor Cost/Hour$27.00Part I1) If the company used a chase demand startegy and rounded any fractional number of employees to the nearest whole number, how many employees would be used in each quarter?2) If the company used a level capacity strategy and rounded any fractional number of employees to the nearest whole number, how many employees would be used?Period1234Forecast1500120021001650Hours Req.Workers Req.Workers UsedPart IIAssume the company wants to use a Level Capacity Strategy with 14 employees (Round the Production in each period to the nearest whole number). In any period where on-hand inventory and production do not meet demand the company would supplement with overtime production. Use the table below to calculate the total costs associated with using this plan. Q3) What would the overtime production cost be for this plan?Q4) What would theTotal Cost be for this plan?Level Capacity Aggregate PlanPeriod1234Forecast1500120021001650Workers Used14141414Hire/(Fire)ProductionProduction - ForecastBeginning InventoryEnding InventoryAverage InventoryOvertime ProductionTotal CostHiring CostFiring CostReg. OutputO.T.SubcontractInventoryBackorderTotal Cost:Total Cost For Plan
Sheet3
WRITING PROJECT 3: ANNOTATED BIBLIOGRAPHY
Description
OVERVIEW: For your Writing Project 3, Annotated Bibliography, you will find, select, and annotate at least 7 relevant, up-to-date, and credible sources which respond to an issue, problem, or controversy related in some way to core readings and which provide information and perspectives that will assist you in answering one or more specific research questions. This project is linked with the next project in the sequence. The sources and perspectives you collect in Writing Project 3 will provide you with the knowledge and evidence you need to take an informed position on your topic in Writing Project 4, Argument. For now, you will focus on exploring your topic, collecting relevant information, formally describing and annotating the sources you collect, and synthesizing information from your sources in a Topic Exploration Statement of your Annotated Bibliography.
1
Explore
the topic
An Annotated Bibliography is a type of formal academic composition required in many classes. In this class, your Annotated Bibliogr.
System and Problem for a Library Management System .docxmattinsonjanel
System and Problem
for a
Library Management System
Smallsville, USA
Our public library in Smallsville is in need of a computer system to
help keep track of who checks books in and out, as well as to keep
track of fines and print reports for us. We have been making out fine
for years recording the information by hand, but Sally and Mary just
don’t have the handwriting they used to, especially at 72 and 81,
respectively. Our new librarian, Marcus, is young and energetic, and
just doesn’t have the patience to keep handwritten records. As head
librarian he wants to be able to do more for our community than just
keep track of books, so he wants to be able to mail out notices of
special events and the like.
Therefore, he has made note of the items he thinks need to be
included in this system. Keep in mind that he knows very little about
computers, so he has probably left some things out. Please feel free
to make any additions or corrections that you feel are absolutely
necessary. Also bear in mind that we are a small town, and do not
have an unlimited budget for such a system or the training required
to use it. A single PC should suffice for our needs right now, but we
might want to grow to two or three, connected together, in a couple
of years.
Here are the main items that are needed:
a. Add a new library patron and be able to edit their basic
information
b. Remove a patron. Ensure that the patron has no books borrowed
and no unpaid fines before deleting them. Provide notice
appropriately.
c. Print a list of all patrons (in some sensible order).
d. Print a list of all patrons with outstanding fines.
e. Add a new book to the catalog. Be able to edit basic book info.
f. Remove a book from the catalog. Ensure no one has it borrowed.
Notify appropriately and do not delete if out.
g. Record a book as lost.
h. Record that a particular patron is borrowing a particular book.
i. Record that someone has returned a particular book. Report any
fines owing and update patron account.
j. Record that a patron has paid some money toward his or her
outstanding fines.
k. Print all overdue books, and who has them.
l. Print address mailing labels
Do not attempt to provide card catalog services for allowing patrons
to search for books, although we may want to expand the system
later to include this capability with multiple stations. You may
assume each book has a unique acquisition number, and you may
use these numbers to refer to books borrowed and returned. For
each book, record acquisition number, title, author and any other
information you need to process the above commands.
For patrons include name, complete address, a unique ID number,
phone number, email and any other info you need to complete the
tasks
In the future we may also engage in inter-library loans with
neighboring cities, and would like to consider self-check stations in
the future since we have a ra ...
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the
Corporate Financial Strategy (BUSI4402) 2020/21
Individual Coursework
Part 1:
(a) What factors might determine the extent to which a firm has fixed rate debt on its balance sheet? Your discussion should include the firm specific and economy wide factors that might influence the percentage of fixed rate debt. (20 marks)
(b) Critically evaluate the survey and empirical evidence in relation to the fixed-floating interest rate structure decision. (20 marks)
Part 2:
(a) Explain the meaning of fair value risk and cash flow risk in relation to the use of debt by non-financial firms. (5 marks)
(b) Explain the meaning of fair value hedging and cash flow hedging in relation to the use of interest rate swaps by non-financial firms. (5 marks)
(c) Using data and information contained in the annual reports you have been assigned, describe and where possible quantify the interest rate risk faced by the firms. You should attempt to use data/information from annual reports over the period 2015 to 2020. You can also source data for your firms from a financial database. (20 marks)
Hints: Your discussion should include where possible the following:
(i) An assessment of whether the firm’s cash flows or profits are in any way correlated with market rates of interest and if so the sign of the correlation. No calculations required.
(ii) Does the firm have borrowings?
(iii) What is the relative size of these borrowings or other measures of the extent of the firm’s financial obligations? Does the firm disclose its leverage ratios? If not try to calculate them. How do they compare with the industry average?
(iv) Is the firm able to generate cash/profits so that it can pay its financial obligations? Does the firm disclose its interest coverage ratios? If not try to calculate them. How do they compare with the industry average?
(v) Is the interest payment on the borrowings a fixed or floating rate?
(vi) What is the percentage of fixed or floating rate debt before the effect of hedging? If possible provide this data from 2015 to 2020.
(vii) What are the trends in various financial obligations ratios? (Leverage, interest coverage ratios etc)
(d) Using data and information contained in your firms annual reports describe and explain the interest rate hedging strategy employed by the firms. (30 marks)
Hints: Your discussion should include where possible the following:
(i) Relate back to part 2 c) on the interest risk faced by your firm.
(ii) Does the firm have a target for the fixed-floating interest rate debt structure? What is this target ratio? Does the firm provide a reason for this target ratio?
(iii) Which types of interest rate hedging instruments is the firm using?
(iv) Explain whether the firm is carrying out a fair value or cash flow interest rate hedging strategy. Is the firm swapping into fixed rate or floating rate debt? Is it doing a bit of both? If you cannot determine then indicate this.
(v) Explain why the particular hedging stra ...
FOR MORE CLASSES VISIT
www.cbr600rank.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write
Agg PlansThe owner of a small mill-working plant that builds cabin.docxnettletondevon
Agg PlansThe owner of a small mill-working plant that builds cabinets is developing his aggregate plan for the next year. The relevant cost data and forecast for the next 4 quarters is provided below. The company currently has 12 employees and works one 8 hour shift each day with 2 paid 15 minute breaks. Assume each quarter has 65 working days, and that it currently has no units in stock. Use this information and the information from the table to answer the questions below. CostsForecastOther DataHolding Cost/Unit/Quarter$25.00Qtr 11500Labor Hours/Unit4.5Hiring Cost$2,500.00Qtr 21200Beginning Inventory0Layoff Cost$3,500.00Qtr 32100Subcontract Cost$135.00Qtr 41650Avg. Labor Cost/Hour$18.00Overtime Labor Cost/Hour$27.00Part I1) If the company used a chase demand startegy and rounded any fractional number of employees to the nearest whole number, how many employees would be used in each quarter?2) If the company used a level capacity strategy and rounded any fractional number of employees to the nearest whole number, how many employees would be used?Period1234Forecast1500120021001650Hours Req.Workers Req.Workers UsedPart IIAssume the company wants to use a Level Capacity Strategy with 14 employees (Round the Production in each period to the nearest whole number). In any period where on-hand inventory and production do not meet demand the company would supplement with overtime production. Use the table below to calculate the total costs associated with using this plan. Q3) What would the overtime production cost be for this plan?Q4) What would theTotal Cost be for this plan?Level Capacity Aggregate PlanPeriod1234Forecast1500120021001650Workers Used14141414Hire/(Fire)ProductionProduction - ForecastBeginning InventoryEnding InventoryAverage InventoryOvertime ProductionTotal CostHiring CostFiring CostReg. OutputO.T.SubcontractInventoryBackorderTotal Cost:Total Cost For Plan
Sheet3
WRITING PROJECT 3: ANNOTATED BIBLIOGRAPHY
Description
OVERVIEW: For your Writing Project 3, Annotated Bibliography, you will find, select, and annotate at least 7 relevant, up-to-date, and credible sources which respond to an issue, problem, or controversy related in some way to core readings and which provide information and perspectives that will assist you in answering one or more specific research questions. This project is linked with the next project in the sequence. The sources and perspectives you collect in Writing Project 3 will provide you with the knowledge and evidence you need to take an informed position on your topic in Writing Project 4, Argument. For now, you will focus on exploring your topic, collecting relevant information, formally describing and annotating the sources you collect, and synthesizing information from your sources in a Topic Exploration Statement of your Annotated Bibliography.
1
Explore
the topic
An Annotated Bibliography is a type of formal academic composition required in many classes. In this class, your Annotated Bibliogr.
System and Problem for a Library Management System .docxmattinsonjanel
System and Problem
for a
Library Management System
Smallsville, USA
Our public library in Smallsville is in need of a computer system to
help keep track of who checks books in and out, as well as to keep
track of fines and print reports for us. We have been making out fine
for years recording the information by hand, but Sally and Mary just
don’t have the handwriting they used to, especially at 72 and 81,
respectively. Our new librarian, Marcus, is young and energetic, and
just doesn’t have the patience to keep handwritten records. As head
librarian he wants to be able to do more for our community than just
keep track of books, so he wants to be able to mail out notices of
special events and the like.
Therefore, he has made note of the items he thinks need to be
included in this system. Keep in mind that he knows very little about
computers, so he has probably left some things out. Please feel free
to make any additions or corrections that you feel are absolutely
necessary. Also bear in mind that we are a small town, and do not
have an unlimited budget for such a system or the training required
to use it. A single PC should suffice for our needs right now, but we
might want to grow to two or three, connected together, in a couple
of years.
Here are the main items that are needed:
a. Add a new library patron and be able to edit their basic
information
b. Remove a patron. Ensure that the patron has no books borrowed
and no unpaid fines before deleting them. Provide notice
appropriately.
c. Print a list of all patrons (in some sensible order).
d. Print a list of all patrons with outstanding fines.
e. Add a new book to the catalog. Be able to edit basic book info.
f. Remove a book from the catalog. Ensure no one has it borrowed.
Notify appropriately and do not delete if out.
g. Record a book as lost.
h. Record that a particular patron is borrowing a particular book.
i. Record that someone has returned a particular book. Report any
fines owing and update patron account.
j. Record that a patron has paid some money toward his or her
outstanding fines.
k. Print all overdue books, and who has them.
l. Print address mailing labels
Do not attempt to provide card catalog services for allowing patrons
to search for books, although we may want to expand the system
later to include this capability with multiple stations. You may
assume each book has a unique acquisition number, and you may
use these numbers to refer to books borrowed and returned. For
each book, record acquisition number, title, author and any other
information you need to process the above commands.
For patrons include name, complete address, a unique ID number,
phone number, email and any other info you need to complete the
tasks
In the future we may also engage in inter-library loans with
neighboring cities, and would like to consider self-check stations in
the future since we have a ra ...
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the
Corporate Financial Strategy (BUSI4402) 2020/21
Individual Coursework
Part 1:
(a) What factors might determine the extent to which a firm has fixed rate debt on its balance sheet? Your discussion should include the firm specific and economy wide factors that might influence the percentage of fixed rate debt. (20 marks)
(b) Critically evaluate the survey and empirical evidence in relation to the fixed-floating interest rate structure decision. (20 marks)
Part 2:
(a) Explain the meaning of fair value risk and cash flow risk in relation to the use of debt by non-financial firms. (5 marks)
(b) Explain the meaning of fair value hedging and cash flow hedging in relation to the use of interest rate swaps by non-financial firms. (5 marks)
(c) Using data and information contained in the annual reports you have been assigned, describe and where possible quantify the interest rate risk faced by the firms. You should attempt to use data/information from annual reports over the period 2015 to 2020. You can also source data for your firms from a financial database. (20 marks)
Hints: Your discussion should include where possible the following:
(i) An assessment of whether the firm’s cash flows or profits are in any way correlated with market rates of interest and if so the sign of the correlation. No calculations required.
(ii) Does the firm have borrowings?
(iii) What is the relative size of these borrowings or other measures of the extent of the firm’s financial obligations? Does the firm disclose its leverage ratios? If not try to calculate them. How do they compare with the industry average?
(iv) Is the firm able to generate cash/profits so that it can pay its financial obligations? Does the firm disclose its interest coverage ratios? If not try to calculate them. How do they compare with the industry average?
(v) Is the interest payment on the borrowings a fixed or floating rate?
(vi) What is the percentage of fixed or floating rate debt before the effect of hedging? If possible provide this data from 2015 to 2020.
(vii) What are the trends in various financial obligations ratios? (Leverage, interest coverage ratios etc)
(d) Using data and information contained in your firms annual reports describe and explain the interest rate hedging strategy employed by the firms. (30 marks)
Hints: Your discussion should include where possible the following:
(i) Relate back to part 2 c) on the interest risk faced by your firm.
(ii) Does the firm have a target for the fixed-floating interest rate debt structure? What is this target ratio? Does the firm provide a reason for this target ratio?
(iii) Which types of interest rate hedging instruments is the firm using?
(iv) Explain whether the firm is carrying out a fair value or cash flow interest rate hedging strategy. Is the firm swapping into fixed rate or floating rate debt? Is it doing a bit of both? If you cannot determine then indicate this.
(v) Explain why the particular hedging stra ...
FOR MORE CLASSES VISIT
www.cbr600rank.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires
For more course tutorials visit
www.newtonhelp.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the structural process of writing. You will refresh basic writing skills and rediscover the building blocks that you will use for longer projects. Consider this a first step in your journey.
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the structural process of writing. You will refresh basic writing skills and rediscover the building blocks that you will use for longer projects. Consider this a first step in your journey.
For more course tutorials visit
www.newtonhelp.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the structural process of writing. You will refresh basic writing skills and rediscover the building blocks that you will use for longer projects. Consider this a first step in your journey.
CBR 600 Effective Communication - snaptutorial.comdonaldzs1
For more classes visit
www.snaptutorial.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent
CBR 600 Imagine Your Future/newtonhelp.com bellflower39
For more course tutorials visit
www.newtonhelp.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the structural process of writing. You will refresh basic writing skills and rediscover the building blocks that you will use for longer projects. Consider this a first step in your journey.
CBR 600 Life of the Mind/newtonhelp.com llflowerbe
For more course tutorials visit
www.newtonhelp.com
Project 1: In this project, you will write a short essay that reflects your belief or passion about a particular part of your professional experience. This project requires you to organize complex and divergent thoughts to write a single page paragraph by paragraph. Your essay is intentionally limited to 500 words to engage you in the structural process of writing. You will refresh basic writing skills and rediscover the building blocks that you will
ACCT 424 Advanced Accounting Final Course Report Resea.docxbartholomeocoombs
ACCT 424 Advanced Accounting
Final Course Report: Research Tracker & Bibliographic Report
General Information:
Project Objective: Create an annotated bibliographic report to meet an assignment from your supervisor after first
creating and using a research tracker. These are two separate deliverables required for this activity.
Why Are We Doing This?: In addition to assessing your performance in this course, this assignment will be used to assess
the accounting program's achievement of program outcomes for the Information Literacy (INFO) Core Learning Area (CLA),
as described in the university's Program Assessment Plan. The INFO CLA is defined as follows: demonstrate an ability to
use libraries and other information resources to effectively locate, select, and evaluate needed information. The
accounting program outcomes are defined as the ability to research accounting information to solve business problems
and improve decision making.
Learning Objective: Demonstrate the ability to use academic and professional databases to research and support
recommendations on emerging accounting issues.
Requirements:
Overview: We learn about a variety of topic in ACCT 424 Advanced Accounting, including the very important topic of
accounting for business mergers and acquisitions (M&As). In addition to the “debit and credits” of M&As there is a host
of activities an accountant would be involved in if they get involved in M&As in practice. One such activity is that of Due
Diligence. By performing this activity, you will not only accomplish required learning objectives, you will also develop an
understanding of what Due Diligence is, a very important topic to have some knowledge about in practice.
The Scenario: Place yourself in the role of a new team member at an organization that’s just begun the process of
negotiating being acquired by another company. Your team lead as come to you and your co-workers and told you that in
a month’s time the other company will be starting the process of Due Diligence, and your team is going to need to support
that effort. Well, your company has never been bought out before, so this whole process is new to everyone, including
this Due Diligence thing.
Since your team lead knows you successfully completed Advanced Accounting at UMUC, she knows you’re the best of the
best and as such she assigns you the task of researching Due Diligence, and wants you to report back to the team with
two specific deliverables: a Research Tracker and an Annotated Bibliography.
Part I – The Research Tracker
A Research Tracker is a straight forward activity that can be thought of as something that simply “tells the story” of your
thought process and logic used in finding information on a subject. In our case, that subject is going to be Due Diligence.
Your requirement for the Research Tracker deliverable will be to research the subject of Due Diligence and create a basic
Research Tracker to rep.
TITLE OF PROPOSAL [typed in all capital letters, double-space.docxgertrudebellgrove
TITLE OF PROPOSAL
[typed in all capital letters, double-spaced and centered]
by
NAME OF STUDENT
This proposal is being submitted in partial fulfillment of the requirements for the Bachelor of Science degree in Public Safety
The Greatest College Jacksonville
Jacksonville, Florida
Fall, 2018
ABSTRACT
The Abstract should be a concise statement of your proposal. It should be no more than one page long. It should be done once you have written the entire paper.
TABLE OF CONTENTS
Abstract
Chapter 1 Introduction
Chapter 2 Review of Literature
Chapter 3 Methodology and Procedure
References
Chapter One
Introduction
Instructions: Begin your chapter with a paragraph that tells the “big picture” view of the problem using a quote from a research study someone else conducted related to your topic.
Background Context
Statement of Problem
Purpose of Research
The purpose of the research is to ____________________________________________. The main co-researchers would be ____________________________________________. The primary research question is: __________________________________________________? The sub-questions for research include: 1) _________________________________________? 2) _________________________________________________________________________? 3) _________________________________________________________________________?
Significance of Research
Chapter Two
Review of Literature
Instructions: Begin your chapter with a paragraph that tells the purpose of your research, the research questions and how you organized your review.
The purpose of the research is to ____________________________________________. The primary research question is: _________________________________________________? The sub-questions for research include: 1) _________________________________________? 2) _________________________________________________________________________? 3) _________________________________________________________________________?A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question. The Review of Literature investigates primary studies related to the following topics connected to my research questions:1) Topic 1; 2) Topic 2; and 3) Topic 3. Also, an explanation of research, the selected methodology, is included.
Topic 1
Topic 2
Topic 3
Framework for Research and Summary of Following Chapters
Chapter Three
Methodology
Instructions: Begin your chapter with a paragraph that tells the purpose of your research, the research questions and how you organized this chapter to include: Rationale for the methods selected and literature references, Definition of population and selection of sample, Procedures for data collection, Procedures and Methods for analysis and synthesis of data, Limitations of study, and Timeline.
The p.
Com 106 Enthusiastic Study / snaptutorial.comStephenson36
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to practice conducting different types of searches.
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to practice conducting different types of searches.
A step by step guide to report writing Step 1 Choose your top.docxannetnash8266
A step by step guide to report writing
Step 1 Choose your topic
If you are given a list of topics from which to choose, select the one that interests you the most or that may have relevance to your chosen career.
If you are allowed to create your own report topic choose a subject that you want to learn more about and that interests you or is a current problem in your workplace that you wish to address.
Step 2 Read the instructions relating to your assessments as set down in your Course Guide
Always check your course guide to ensure that you are clear about what you are required to do.
• When is the report due?
• How long is it?
• What is the format?
• What is the structure?
• How does this topic relate to the course?
• How does this topic relate to the current area being studied?
Step 3 Analyse the topic
Break the topic into its component parts to understand what the main issue is that must be addressed.
Report topics can usually be divided into three sections:
• Content What is the issue or problem to be addressed?
• Instruction What have you been asked to do in relation to the topic?
• Scope How has the topic been limited – is there a focus on particular organisations/ countries /year(s)?
Underline key words and draw circles around the action/instruction words.
It is really important that you understand what the instruction words are telling you to do.
Step 4 Brain storm – what do you already know about the issue?
A brainstorm is the beginning of a mind map – these random ideas can be organised into a structured mind map that will provide you with a guide for your research and your writing.
• Using your reading, lectures and your own experiences think about what you already know about the problem/issue.
• On a blank piece of paper, write down all the ideas that you think might be related to the subject under review
• Write down where you think you need to go to get information other than from books, journals websites etc. Think about who you know in business who you might be able to interview.
Step 5 Starting your research
Although you are required to read and research widely, it is better to gain an overview of the topic by firstly reading the recommended texts – don’t go straight online unless instructed to do so by your lecturer or tutor.
The texts will give you a broad understanding of .the main ideas, writers and theories associated with the issue.
By familiarising yourself with the key concepts, the next stage of your investigation will be more targeted.
Step 6 Mind mapping
A mind map is a visual way of gathering your ideas about a particular topic.
Mind maps help you to identify the main ideas and what research needs to be conducted to provide the evidence that supports these ideas.
Your mind map is a good time management resource. It will help you focus your search for information more efficiently and to organise your ideas into a coherent and logical structure when you write your .
For more classes visit
www.snaptutorial.com
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to
Jan 18, 2013 at 217pmNo unread replies.No replies.Post yo.docxlmelaine
Jan 18, 2013 at 2:17pm
No unread replies.
No replies.
Post your definition of the apostrophe as you derived it from the section on the apostrophe in LB pages 316 - 322. What surprised you about the apostrophe? Give at least 2 examples of correct usage of the apostrophe from your own writing. Give examples of badly used apostrophes you have seen in public writing. Indicate the rule that determines correct usage
.
Jan 10, 20141.Definition of law A set of rules and proced.docxlmelaine
Jan 10, 2014
1.
Definition of law:
A set of rules and procedures usually intended to regulate some aspect of society.
(
Joanne B, H. (2010).
Introduction to law
. (4th ed., Vol. Edition). (Page 2)
2.
What are some historical origins of a civil law legal system?
3.
Identify the historical origin of a common law legal system.
4.
What is the difference between a civil law legal system and a common law legal system?
5.
What is meant by jurisprudence?
6.
Describe three major philosophical theories of law.
This is the 1st weeks assignment....will send the rest by the week until week 7 also Midterm and Final.
.
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CBR 600 Effective Communication - snaptutorial.comdonaldzs1
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ACCT 424 Advanced Accounting Final Course Report Resea.docxbartholomeocoombs
ACCT 424 Advanced Accounting
Final Course Report: Research Tracker & Bibliographic Report
General Information:
Project Objective: Create an annotated bibliographic report to meet an assignment from your supervisor after first
creating and using a research tracker. These are two separate deliverables required for this activity.
Why Are We Doing This?: In addition to assessing your performance in this course, this assignment will be used to assess
the accounting program's achievement of program outcomes for the Information Literacy (INFO) Core Learning Area (CLA),
as described in the university's Program Assessment Plan. The INFO CLA is defined as follows: demonstrate an ability to
use libraries and other information resources to effectively locate, select, and evaluate needed information. The
accounting program outcomes are defined as the ability to research accounting information to solve business problems
and improve decision making.
Learning Objective: Demonstrate the ability to use academic and professional databases to research and support
recommendations on emerging accounting issues.
Requirements:
Overview: We learn about a variety of topic in ACCT 424 Advanced Accounting, including the very important topic of
accounting for business mergers and acquisitions (M&As). In addition to the “debit and credits” of M&As there is a host
of activities an accountant would be involved in if they get involved in M&As in practice. One such activity is that of Due
Diligence. By performing this activity, you will not only accomplish required learning objectives, you will also develop an
understanding of what Due Diligence is, a very important topic to have some knowledge about in practice.
The Scenario: Place yourself in the role of a new team member at an organization that’s just begun the process of
negotiating being acquired by another company. Your team lead as come to you and your co-workers and told you that in
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TITLE OF PROPOSAL [typed in all capital letters, double-space.docxgertrudebellgrove
TITLE OF PROPOSAL
[typed in all capital letters, double-spaced and centered]
by
NAME OF STUDENT
This proposal is being submitted in partial fulfillment of the requirements for the Bachelor of Science degree in Public Safety
The Greatest College Jacksonville
Jacksonville, Florida
Fall, 2018
ABSTRACT
The Abstract should be a concise statement of your proposal. It should be no more than one page long. It should be done once you have written the entire paper.
TABLE OF CONTENTS
Abstract
Chapter 1 Introduction
Chapter 2 Review of Literature
Chapter 3 Methodology and Procedure
References
Chapter One
Introduction
Instructions: Begin your chapter with a paragraph that tells the “big picture” view of the problem using a quote from a research study someone else conducted related to your topic.
Background Context
Statement of Problem
Purpose of Research
The purpose of the research is to ____________________________________________. The main co-researchers would be ____________________________________________. The primary research question is: __________________________________________________? The sub-questions for research include: 1) _________________________________________? 2) _________________________________________________________________________? 3) _________________________________________________________________________?
Significance of Research
Chapter Two
Review of Literature
Instructions: Begin your chapter with a paragraph that tells the purpose of your research, the research questions and how you organized your review.
The purpose of the research is to ____________________________________________. The primary research question is: _________________________________________________? The sub-questions for research include: 1) _________________________________________? 2) _________________________________________________________________________? 3) _________________________________________________________________________?A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question. The Review of Literature investigates primary studies related to the following topics connected to my research questions:1) Topic 1; 2) Topic 2; and 3) Topic 3. Also, an explanation of research, the selected methodology, is included.
Topic 1
Topic 2
Topic 3
Framework for Research and Summary of Following Chapters
Chapter Three
Methodology
Instructions: Begin your chapter with a paragraph that tells the purpose of your research, the research questions and how you organized this chapter to include: Rationale for the methods selected and literature references, Definition of population and selection of sample, Procedures for data collection, Procedures and Methods for analysis and synthesis of data, Limitations of study, and Timeline.
The p.
Com 106 Enthusiastic Study / snaptutorial.comStephenson36
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to practice conducting different types of searches.
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to practice conducting different types of searches.
A step by step guide to report writing Step 1 Choose your top.docxannetnash8266
A step by step guide to report writing
Step 1 Choose your topic
If you are given a list of topics from which to choose, select the one that interests you the most or that may have relevance to your chosen career.
If you are allowed to create your own report topic choose a subject that you want to learn more about and that interests you or is a current problem in your workplace that you wish to address.
Step 2 Read the instructions relating to your assessments as set down in your Course Guide
Always check your course guide to ensure that you are clear about what you are required to do.
• When is the report due?
• How long is it?
• What is the format?
• What is the structure?
• How does this topic relate to the course?
• How does this topic relate to the current area being studied?
Step 3 Analyse the topic
Break the topic into its component parts to understand what the main issue is that must be addressed.
Report topics can usually be divided into three sections:
• Content What is the issue or problem to be addressed?
• Instruction What have you been asked to do in relation to the topic?
• Scope How has the topic been limited – is there a focus on particular organisations/ countries /year(s)?
Underline key words and draw circles around the action/instruction words.
It is really important that you understand what the instruction words are telling you to do.
Step 4 Brain storm – what do you already know about the issue?
A brainstorm is the beginning of a mind map – these random ideas can be organised into a structured mind map that will provide you with a guide for your research and your writing.
• Using your reading, lectures and your own experiences think about what you already know about the problem/issue.
• On a blank piece of paper, write down all the ideas that you think might be related to the subject under review
• Write down where you think you need to go to get information other than from books, journals websites etc. Think about who you know in business who you might be able to interview.
Step 5 Starting your research
Although you are required to read and research widely, it is better to gain an overview of the topic by firstly reading the recommended texts – don’t go straight online unless instructed to do so by your lecturer or tutor.
The texts will give you a broad understanding of .the main ideas, writers and theories associated with the issue.
By familiarising yourself with the key concepts, the next stage of your investigation will be more targeted.
Step 6 Mind mapping
A mind map is a visual way of gathering your ideas about a particular topic.
Mind maps help you to identify the main ideas and what research needs to be conducted to provide the evidence that supports these ideas.
Your mind map is a good time management resource. It will help you focus your search for information more efficiently and to organise your ideas into a coherent and logical structure when you write your .
For more classes visit
www.snaptutorial.com
Throughout the course of your academic career, you will be asked to conduct research to support the assertions you make in papers, presentations, and projects. Sometimes getting at the material you will need is fairly straightforward, while other times the research process forces you to get a little creative in seeking out (and finding) the types of source material that will be most useful to you. This exercise will allow you to
Jan 18, 2013 at 217pmNo unread replies.No replies.Post yo.docxlmelaine
Jan 18, 2013 at 2:17pm
No unread replies.
No replies.
Post your definition of the apostrophe as you derived it from the section on the apostrophe in LB pages 316 - 322. What surprised you about the apostrophe? Give at least 2 examples of correct usage of the apostrophe from your own writing. Give examples of badly used apostrophes you have seen in public writing. Indicate the rule that determines correct usage
.
Jan 10, 20141.Definition of law A set of rules and proced.docxlmelaine
Jan 10, 2014
1.
Definition of law:
A set of rules and procedures usually intended to regulate some aspect of society.
(
Joanne B, H. (2010).
Introduction to law
. (4th ed., Vol. Edition). (Page 2)
2.
What are some historical origins of a civil law legal system?
3.
Identify the historical origin of a common law legal system.
4.
What is the difference between a civil law legal system and a common law legal system?
5.
What is meant by jurisprudence?
6.
Describe three major philosophical theories of law.
This is the 1st weeks assignment....will send the rest by the week until week 7 also Midterm and Final.
.
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Jacob claims the employer violated his rights. In your opinion, what.docxlmelaine
Jacob claims the employer violated his rights. In your opinion, what are the legal rights of the employer and the employee in this situation? Explain. Is Jacob correct in his allegations? Why or why not?
Since Jacob believes he was wrongfully terminated and various rights were violated, he plans to consult with a lawyer and sue Cranes. What are Jacob's options with regards to resolving his claims through the court or ADR?
Jacob claims the state troopers violated his rights. Do you agree?
Has Brianna committed any offenses? Why or why not?
Did Lucy violate intellectual property laws? If yes, how? If no, why not?
Has Jacob committed any violations in his Internet postings concerning his former company? Why or why not?
What are the ethical issues related to this scenario?
Support your responses with examples.
Cite any sources in APA format.
.
Ive been promised A+ papers in the past but so far I have not seen .docxlmelaine
I've been promised A+ papers in the past but so far I have not seen better than a C. Is there anyone out there that can do this and seriously get an A or atleast a B. I would greatly appreciate :)
In a 1-2 page Microsoft Word document, discuss the following case study:
When Alexander and Deborah married, Alexander owned a duplex in a community property state. They lived in one side of the duplex. They saved their money and bought a lake lot as tenants by the entirety. Deborah failed to pay the loans she took out from Savings Bank prior to her marriage to pay for college. The bank claimed the duplex, the lake lot and their savings.
Discuss the likelihood of success on the bank's claims against the properties.
.
It’s easy to dismiss the works from the Dada movement as silly. Cons.docxlmelaine
It’s easy to dismiss the works from the Dada movement as silly. Consider the art that was popular at the time, however. These “silly” works were a violent protest to the realism and impressionism of the day. Check out “Entr' acte", 1924, directed by Rene Clair” on YouTube, if you can, for an excellent example of Dada.
www.youtube.com/watch?v=NMaXF-4MMGA
The pointlessness of the action is the point! I still crack up at the end even seen it hundreds of times.
Think: what does Dada do that realism cannot? What’s the value of a movement that breaks all the rules? What did Dada contribute to the progress of art and film?
Remember, post before WEDNESDAY and three times during the week because you must contribute three postings over the week for full credit. Please write more than 50 words for your first response to my question.
Posted by William Ousley at 06/17/13 11:24
What Dada can do that realism cannot is make humorous, chaotic assemblage of events. The value of a movement that breaks all the rules is a non-traditional valued movement. The Dada anti-art movement had a strong negative and destructive element. Dada writers and artists were concerned with shock, protest, and nonsense. Dada contributed to assemblage, collage, photomontage and the use of ready-made objects. The inclusion of sound in art, the incorporation of found objects in a work of art, and the concept of improvising as a performance options were all substantially important to not only the development of music, but more specifically the development of electronic music.
(1)
Posted by Anya Walker at 06/20/13 03:10
William
The art of film is very dynamic. Dada was a great way to show how it was used. I know watching the film showed so many scenes and object so, it made it very helpful to understand the meaning of Dada.
Posted by Anya Walker at 06/18/13 05:59
Dada is hilarious to watch. The artist is able to show realism by having creative scenes that was part of the anti-war movement era. The objective of using a technique called collage was used by combining different type of scraps that was part of illustration to be viewed in different scenes. Dada contributes to the art of film by having music being played while watching the film. Also, surrealism was introduced to show a type of chaotic way of using humorous scenes in film.
(2)
Posted by William Ousley at 06/18/13 09:55
Anya
Very well written. For some reason I read and read the article on Dada in the book and couldn't quite get it. So I read a few articles from the Internet to fully understand what the Dada movement was. Even with breaking all the rules they were able to contribute to the art.
Posted by Byron Stival at 06/21/13 06:05
Anya-
It is fun to watch this video. Some of it was funny but I also had a hard time watching all of it. I like the first introduction to the music. I love music and love to think of what the person was thinking and feeling when they wrote the music. It baffles my mind that someone ca.
Its meaning is still debated. It could be a symbol of the city of Fl.docxlmelaine
Its meaning is still debated. It could be a symbol of the city of Florence (and by association of the Medici's identification with the city of Florence) or it could be a metaphor for the nature of love. Choose one of these meanings and elaborate on that meaning. Be sure to talk about the story of David, how he is portrayed in the statue, its location, etc.
.
Jaffe and Jordan want to use financial planning models to prepar.docxlmelaine
Jaffe and Jordan want to use financial planning models to prepare a projected (pro forma) financial statement to determine the profitability and financial health of the business for next year, ending Dec 31, 2021. Use the pro forma financial statement below to answer the following questions:
PRO FORMA INCOME STATEMENT
($millions)
Total operating revenues
82
Less expenses
27
Less depreciation
9
Earnings before interest and taxes
46
Less interest
4
Net income before taxes
42
Less taxes @ 23.8%
10
Net income
32
PRO FORMA BALANCE SHEET
Assets:
Cash
19
Other current assets
28
Net Fixed Assets
40
Total Assets
87
Liabilities and Equities:
Accounts payable
12
Long-term debt
28
Stockholders' Equity
47
Total Liabilities & Equities
87
a. What is the
estimated profit
of the business for 2021?
b. Compute the following
profitability ratios
and explain to Jaffe and Jordan whether the business looks profitable relative to the performance of the industry.
i. Profit margin
ii. Return on assets
iii. Return on equity
iv. calculate and explain operating cash flow
The industry ratios are as follows:
Industry ratios
Profit margin
32.80%
Return on assets
34.00%
Return on equity
42.50%
c. Assuming you project a 25% increase in
operating revenue
(sales) per year what will be the anticipated operating revenue in 2022?
d. If net income is projected to increase by 20% per year, what will be the
profit margin
in 2022?
e. What will be the estimated
earnings per share
(EPS) in 2022 if 1,000,000 shares are issued?
.
Ive got this assinment due and was wondering if anyone has done any.docxlmelaine
I've got this assinment due and was wondering if anyone has done anything similar?? If so can easily change around information and will make it much easier to do it a second time round.
Please read this extremely carefully!
THIS NEEDS TO BE DONE OVER A 7-10 DAY PERIOD!!! please do not message me unless you UNDERSTAND exactly what needs to be done, and the extent of needing to bring in other scholars and research! THIS ASSIGNMENT NEEDS SOMEONE WHO'S ENGLISH IS PERFECT!! when messaging let me know what you believe needs to be done, so I can see you understand the brief. Let me know if you have any questions, I will be helping you out along the way!!
Content Analysis
Due: 11pm Friday 19 September
Weighting: 30%
This assignment assesses your ability to critique two culturally divergent global television news services by analysing their online news content.
Length: 1500 words.
Carry out a content analysis of Internet television of two reputable news organizations, one Western and one non-Western by studying elements such as language, pictures and headlines in the reporting of international events.
From the data gathered write a comparative analysis of news content focusing on the news agenda, sources and predominant news values.
Do the following:
• Over a 2-week period gather data from the website looking at the news agenda i.e. the top 5 stories covered by subject (i.e. politics, business/economics, conXict, human interest, celebrity) and geographical interest (i.e. North America, Europe, Asia, Latin America, PaciWc)
• Who are the experts quoted? (i.e. their cultural, political or social orientation) Are they from an elite or non-elite country or group?
• From what cultural/national perspectives are the stories being reported?
• Who is the target audience?
• What are the predominant news values?
Your insights and analysis should be supported by examples from the evidence gathered as well as course readings and other literature.
Attach samples of your page views as an appendix to your analysis for each website (no more than 4 pages).
Examples of global news networks your may choose:
• BBC
• Al Jazeera
• CNN
• CCTV
• France24
• Xinhua News Agency
• ABC News World
• TimesNow.tv
Submit your analysis and samples as one document to Turnitin by 11pm Friday 19 September, 2014.
Students will be assessed on their ability to:
• Clearly articulate the aim and method of their research.
• Present robust data, using evidence to build an argument.
• Draw connections from diVerent forms of evidence.
• Structure the essay in a clear, logical and engaging way.
• Provide a strong argument through interpretation of data and reference to relevant
concepts.
• EVectively integrate cited material, with complete and appropriate referencing.
• Write clearly, concisely and directly, without spelling or grammatical errors.
Unit guide ICOM201 International Television and Beyond
This Assessment Task relates to the following Learning Outcomes:
• Demonstrate unde.
It is thought that a metabolic waste product produced by a certain g.docxlmelaine
It is thought that a metabolic waste product produced by a certain group of prokaryotic organisms made possible the evolution of the eukaryotic cell. Name the metabolic waste product and the group of prokaryotic organisms that produce it. Name the metabolic reaction that leads to this waste product being produced. Discuss two ways that the build-up of this waste product helped pave the way for the evolution of higher organisms (plants and animals).
.
it is not the eassay it is about anwering the question with 2,3 pa.docxlmelaine
it is not the eassay it is about anwering the question with 2,3 paragraph.
there is 4 questions
1. Explain how imperialism has changed over time(each catagory need 1,2 sentence description )-
(1) From the early period of Spanish and Portuguese dominations
(2)Through the rise of the Atlantic system,
(3)to the New imperialism of the mid-to-late 19th century,
(4)up to the era of Neo-colonization of the late 20th and 21th century
2. What are the main characteristics of each period?
3. What changed over time?
4. What did not change?
5. In your opinion which system/era was easiest to resist and why?
Write it with easy word.
.
It is now time to select sources and take some notes. You will nee.docxlmelaine
It is now time to select sources and take some notes. You will need to use the Cornell method of note taking to complete your notes. Remember, the more detailed your notes are, the easier it will be to write your paper.
As you take notes, keep track of the sources from where you borrow ideas. Be sure you write down all of the information you will need to cite later in the Works Cited page, in
MLA format
. If you come across a source that you are not sure how to cite, please contact your instructor. Even if you write the information in your own words, it can be considered plagiarism if not cited properly.
Cornell Notes
Topic:
Page ___ of ____.
Name:
Course:
Teacher:
Date:
Main Idea:
Notes:
Summary/Questions:
.
Its a linear equations question...Neilsen Media Research surveys .docxlmelaine
It's a linear equations question...
Neilsen Media Research surveys TV-watching habits and provides a list of the 20 most-watched TV programs each week. Each rating point in the survey represents 1,102,000 households. One week "60 Minutes" had a rating of 11.0. How many households did this represent?
.
itively impact job satisfactionWeek 3 - Learning Team Paper - Due .docxlmelaine
itively impact job satisfaction
Week 3 - Learning Team Paper - Due Day 7
Learning Team Assignment:
Job Satisfaction Paper
Use
the University of Phoenix Library, and/or other resources, to conduct research concerning the concept of job satisfaction.
Prepare
a 1,050 to 1,400-word paper in which you address the following items:
Introduction and Define
job satisfaction
.
·
Explain the impact that organizational socialization has on job satisfaction.
·
Provide an example of how an organization can use organizational socialization to positively impact job satisfaction. -
·
Describe the relationship between organizational commitment and job satisfaction.
·
Provide an example of how an organization can use organizational commitment to positively impact job satisfaction.
My portion
·
Conclusion -
.
It is not an online course so i cannot share any login details. No d.docxlmelaine
It is not an online course so i cannot share any login details. No detailed instructions were given to complete this assignment. The professor indicated that he wants a 3-4 page paper with a topic of my choosing. It needs to be about civilization as a whole though. The two topics i showed to the professor that he agreed were good for the paper were the following:
Discuss the death sentence and how it has been changed over the years morally.
Discuss the use of physical torture and how it has changed over the years morally.
These papers are discussing time periods ranging from the spanish inquisition, all the way up to present day. How were these used in the past and how did our civilization change to accept it the way it is today?
.
IT Strategic Plan, Part 1Using the case provided, analyze the busi.docxlmelaine
IT Strategic Plan, Part 1
Using the case provided, analyze the business environment described to develop Part 1 of an IT Strategic Plan. Identify the business’ strategic objectives, develop an IT mission and vision for the organization, describe an appropriate governance process, and provide an inventory of the organization’s current IT projects. Your analysis will be presented in a short paper that follows the outline provided, using Microsoft Word, or in a format that can be read using MS Word.
Case Study: Wobbly Wheels (WW) Distribution Company
Overview
WW is a regional transportation and distribution company in operation for over 60 years. The company serves major cities in the Mid-Atlantic region. They are headquartered in Wilmington, Delaware and have a staff of 400 employees including truck drivers. There are 6 distribution terminals (Philadelphia PA, Baltimore MD, New York City, Washington DC, Newark NJ and Wilmington DE) for consolidating freight, and 100 delivery vehicles including 20 tractor/semi-trailer units, 40 box trucks and 40 panel vans.
The company operates in a highly competitive business environment. Growth has been stagnant because of a slow economy. John, the president of the company, would like to see growth at 5% per year. He would also like to see expenses cut by 5% to help fund new initiatives. Current revenue is about $39 million a year with profit running at 4%.
Current Business Operations
WW operates 24 hours a day, 7 days a week. Sales personnel (12 people, two per terminal) visit prospective customers to outline company capability, services provided and costs. When a customer decides to use WW they call the dispatch office with shipment information. Usually they FAX a copy of the bill (s) of lading to a terminal with information such as origin, destination, product description, weight and number of packages.
A dispatcher at a terminal makes a list of freight pickups and sends a truck to get the freight. To do this they use the routing system to determine the sequence of pickups by zip code. They use local maps within a zip code to map out the specific order of pickups since there may be several in a zip code area. They have a performance goal of 98% of freight picked up within 24 hours of availability.
A driver follows the dispatch order for pickups. Many of the drivers complain that the pickup order is not efficient. When they pick up an order they sign for receipt and either load the freight or guide the customer’s forklift operators to arrange it properly in the truck.
After freight is picked up it is brought to the terminal where it is unloaded and sorted by destination. A dispatcher then prepares a delivery ticket (again using the routing system) that is used to load a truck in the proper sequence for delivery. Some trucks take freight from one terminal to another while others make local deliveries. About half of a terminal’s space is used on any given night. Dispatchers have a goal to turn freight around.
It should be in API format.Research paper should be on Ethernet .docxlmelaine
It should be in API format.
Research paper should be on
Ethernet Networking
related to my specific subject which is
Telecommunications and networking.
It should be 17-20 pages in length. It should be a complete, polished artifact containing all of the main elements of the final product.
It should be plagiarism free.
It should contain Contexts, abstract, introduction, main body , conclusion and references. And if needed can use graphs or diagrams.
.
IT Strategic Plan, Part 2Using the case provided, build on Part .docxlmelaine
IT Strategic Plan, Part 2
Using the case provided, build on Part 1 of your IT Strategic Plan, and develop Part 2. Develop IT strategies to align to the business strategies, complete a roadmap of the current IT projects, propose a new IT project to support the IT strategies, identify risks associated with the IT projects, and explain the steps required to develop a business continuity plan for the most important IT systems. Your analysis will be presented in a short paper that follows the outline provided, using Microsoft Word, or in a format that can be read using MS Word.
Case Study: Wobbly Wheels (WW) Distribution Company
Overview
WW is a regional transportation and distribution company in operation for over 60 years. The company serves major cities in the Mid-Atlantic region. They are headquartered in Wilmington, Delaware and have a staff of 400 employees including truck drivers. There are 6 distribution terminals (Philadelphia PA, Baltimore MD, New York City, Washington DC, Newark NJ and Wilmington DE) for consolidating freight, and 100 delivery vehicles including 20 tractor/semi-trailer units, 40 box trucks and 40 panel vans.
The company operates in a highly competitive business environment. Growth has been stagnant because of a slow economy. John, the president of the company, would like to see growth at 5% per year. He would also like to see expenses cut by 5% to help fund new initiatives. Current revenue is about $39 million a year with profit running at 4%.
Current Business Operations
WW operates 24 hours a day, 7 days a week. Sales personnel (12 people, two per terminal) visit prospective customers to outline company capability, services provided and costs. When a customer decides to use WW they call the dispatch office with shipment information. Usually they FAX a copy of the bill (s) of lading to a terminal with information such as origin, destination, product description, weight and number of packages.
A dispatcher at a terminal makes a list of freight pickups and sends a truck to get the freight. To do this they use the routing system to determine the sequence of pickups by zip code. They use local maps within a zip code to map out the specific order of pickups since there may be several in a zip code area. They have a performance goal of 98% of freight picked up within 24 hours of availability.
A driver follows the dispatch order for pickups. Many of the drivers complain that the pickup order is not efficient. When they pick up an order they sign for receipt and either load the freight or guide the customer’s forklift operators to arrange it properly in the truck.
After freight is picked up it is brought to the terminal where it is unloaded and sorted by destination. A dispatcher then prepares a delivery ticket (again using the routing system) that is used to load a truck in the proper sequence for delivery. Some trucks take freight from one terminal to another while others make local deliveries. About half of a terminal’s sp.
It seems most everything we buy these days has the label made in Ch.docxlmelaine
It seems most everything we buy these days has the label “made in China”. China has become the second largest world economy, and one of the fastest growing in the world. Discuss the factors that have allowed China to become such a large economy, and the challenges China is likely to face in the near future.
250 words and cited with in .
.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
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Big Data Analytics
iden�fy fundamental concepts of Big Data management
and analy�cs.
become competent in recognizing challenges faced by
applica�ons dealing with very large volumes of data as
well as in proposing scalable solu�ons for them.
be able to understand how Big Data impacts business
intelligence, scien�fic discovery, and our day-to-day life.
Course Descrip�on: In this course the students explore key data
analysis and management
techniques, which applied to massive datasets are the
cornerstone
that enables real-�me decision making in distributed
environments,
business intelligence in the Web, and scien�fic discovery at
large
scale. In par�cular, students examine the map-reduce parallel
compu�ng paradigm and associated technologies such as
distributed
file systems, no-sql databases, and stream compu�ng engines.
This
highly interac�ve course is based on the problem-based
learning
philosophy. Students are expected to make use of technologies
to
design highly scalable systems that can process and analyze Big
Data
for a variety of scien�fic, social, and environmental challenges.
3. Course
Objec�ves/Learner
Outcomes:
Course Objec�ves/Learner Outcomes:
Upon comple�on of this course, the student will:
Prerequisites: There are no prerequisites for this course.
Books and
Resources:
Required Text
EMC Educa�on Service (Eds). (2015) Data Science and Big
Data Analytics:
Discovering, Analyzing, Visualizing, and Presenting Data,
Indianapolis,
IN: John Wiley & Sons, Inc
××
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https://ucumberlands.blackboard.com/webapps/blackboard/exec
ute/courseMain?course_id=_114565_1
CSCI 561
Article Review Instructions
4. After reading through your assignments this week, you are to
pick a topic of interest that was mentioned in the reading
assignment. Using the Jerry Falwell Library and other scholarly
resources, you are to locate a peer reviewed journal related to
the topic of your interest. Read the journal article thoroughly so
you can discuss it. If you wish to use something other than a
peer reviewed journal, please consult with your instructor
before starting the assignment.
You will then prepare an article review related to the topic that
you researched in the research/reading assignments from the
assigned module/week. The article review that you create must
be at least 750words and be formatted according to APA style.
Use the following section order to guide you in building your
article review but do not use the numbers in your section
headers, only the names. Also, this is example is not in APA
style, make sure your review follows APA styles, this is a guide
NOT a template.
1. Bibliographical Reference:
a. Create a single bibliographical entry in APA style in the first
section of your paper. This should include:
i. Detail the author(s) of the article
ii. Name of the Journal (including volume, issue, year, page
numbers, etc.)
iii. Name of the article you are reviewing.
b. Note – You may also choose to identify the article you are
reviewing (i.e. – The focus of this review will be “Article
Name” published in “Journal Name” in “Year/Month”) and then
simply cite it in a bibliographical entry at the end (see section
7).
2. Objectives:
a. After reviewing the article, use a bulleted list to identity the
3 to 5 primary points you feel the article addresses.
b. Simply put the bulleted list of those points in your Objectives
5. section with something to the effect of “After reviewing
“Article Name” the three main points addressed by the author(s)
were:
· Bullet one
· Bullet two
· Bullet three
3. Summary:
a. Summarize the article you reviewed in approximately 2 or 3
full paragraphs.
b. Do not use direct quotes at all. If you need to quote it,
paraphrase what you read.
c. Use the bullets above (section 2b) to structure what you wish
to discuss in this summary (i.e. – In the first paragraph,
summarize the article section which addresses the first bullet in
2b and so on).
4. Results:
a. Now that you have read this article and summarized it, what
do you feel that a reader can learn about the topic from the
article?
b. Using bullet points, highlight the things you feel like you
learned more about after reading this article. It’s best to keep
this list to a maximum of 5 bullets.
c. Note – these bullets should not be identical to the bullets in
the Objective Section (2b).
5. Critique:
a. Use this section to provide an academic critique of the
article.
i. How well (or poorly) was this article written?
ii. Did it accomplish the objectives it set out to do (think back
to the Objectives section)?
iii. Why or why not?
b. Explain your opinion and offer some additional sources (no
6. more than one or two) to support that opinion.
c. When possible, address the subject matter from a biblical
perspective (e.g. – the Bible teaches us to… and this article
addresses that by…)
6. Questions:
a. List a minimum of 3 (no more than 5) questions that arose
from the reading of this article in a numbered list.
b. Consider any thing you feel like you should have learned
from the article but did not.
c. Note – These questions may spark your desire to review other
matter on the topic and may even be used as a starting point for
one of your two research papers (though this is not required).
7. Bibliography:
a. You need to use one other sources to support or deny your
opinion and if you chose to only identify the article in section
1, you will want to make a bibliography.
b. Follow APA guidelines for Bibliographies as outlined in the
APA 6th Edition Guide.
IMPORTANT – Article reviews are DUE by 11:59ET on Sunday
of the assigned Module/Week!
ffirs.indd 2:43:16:PM/12/11/2014 Page i
Data Science &
Big Data Analytics
8. ISBN: 978-1-118-87622-0 (ebk)
ISBN: 978-1-118-87605-3 (ebk)
Manufactured in the United States of America
10 9 8 7 6 5 4 3 2 1
No part of this publication may be reproduced, stored in a
retrieval system or transmitted in any form or by any means,
electronic, mechanical, photocopying,
recording, scanning or otherwise, except as permitted under
Sections 107 or 108 of the 1976 United States Copyright Act,
without either the prior written permis-
sion of the Publisher, or authorization through payment of the
appropriate per-copy fee to the Copyright Clearance Center, 222
Rosewood Drive, Danvers, MA
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Publisher for permission should be addressed to the Permissions
Department, John Wiley & Sons, Inc.,
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(201) 748-6008, or online at
http://www.wiley.com/go/permissions.
Limit of Liability/Disclaimer of Warranty: The publisher and
the author make no representations or warranties with respect to
the accuracy or completeness of
the contents of this work and specifically disclaim all
warranties, including without limitation warranties of fitness for
a particular purpose. No warranty may be
9. created or extended by sales or promotional materials. The
advice and strategies contained herein may not be suitable for
every situation. This work is sold with
the understanding that the publisher is not engaged in rendering
legal, accounting, or other professional services. If professional
assistance is required, the
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Neither the publisher nor the author shall be liable for damages
arising herefrom. The fact that an
organization or Web site is referred to in this work as a citation
and/or a potential source of further information does not mean
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ffirs.indd 2:43:16:PM/12/11/2014 Page v
Credits
Executive Editor
Carol Long
Project Editor
Kelly Talbot
Production Manager
11. Kathleen Wisor
Copy Editor
Karen Gill
Manager of Content Development
and Assembly
Mary Beth Wakefield
Marketing Director
David Mayhew
Marketing Manager
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Professional Technology and Strategy Director
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Associate Publisher
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12. Proofreader
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Indexer
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ffirs.indd 2:43:16:PM/12/11/2014 Page vi
About the Key Contributors
David Dietrich heads the data science education team within
EMC Education Services, where he leads the
curriculum, strategy and course development related to Big Data
Analytics and Data Science. He co-au-
thored the first course in EMC’s Data Science curriculum, two
additional EMC courses focused on teaching
leaders and executives about Big Data and data science, and is a
contributing author and editor of this
book. He has filed 14 patents in the areas of data science, data
privacy, and cloud computing.
David has been an advisor to several universities looking to
develop academic programs related to data
13. analytics, and has been a frequent speaker at conferences and
industry events. He also has been a a guest lecturer at universi-
ties in the Boston area. His work has been featured in major
publications including Forbes, Harvard Business Review, and
the
2014 Massachusetts Big Data Report, commissioned by
Governor Deval Patrick.
Involved with analytics and technology for nearly 20 years,
David has worked with many Fortune 500 companies over his
career, holding multiple roles involving analytics, including
managing analytics and operations teams, delivering analytic
con-
sulting engagements, managing a line of analytical software
products for regulating the US banking industry, and developing
Software-as-a-Service and BI-as-a-Service offerings.
Additionally, David collaborated with the U.S. Federal Reserve
in develop-
ing predictive models for monitoring mortgage portfolios.
Barry Heller is an advisory technical education consultant at
EMC Education Services. Barry is a course developer and cur-
riculum advisor in the emerging technology areas of Big Data
and data science. Prior to his current role, Barry was a consul-
tant research scientist leading numerous analytical initiatives
within EMC’s Total Customer Experience
organization. Early in his EMC career, he managed the
14. statistical engineering group as well as led the
data warehousing efforts in an Enterprise Resource Planning
(ERP) implementation. Prior to joining EMC,
Barry held managerial and analytical roles in reliability
engineering functions at medical diagnostic and
technology companies. During his career, he has applied his
quantitative skill set to a myriad of business
applications in the Customer Service, Engineering,
Manufacturing, Sales/Marketing, Finance, and Legal
arenas. Underscoring the importance of strong executive
stakeholder engagement, many of his successes
have resulted from not only focusing on the technical details of
an analysis, but on the decisions that will be resulting from
the analysis. Barry earned a B.S. in Computational Mathematics
from the Rochester Institute of Technology and an M.A. in
Mathematics from the State University of New York (SUNY)
New Paltz.
Beibei Yang is a Technical Education Consultant of EMC
Education Services, responsible for developing several open
courses
at EMC related to Data Science and Big Data Analytics. Beibei
has seven years of experience in the IT industry. Prior to EMC
she
worked as a software engineer, systems manager, and network
manager for a Fortune 500 company where she introduced
15. new technologies to improve efficiency and encourage
collaboration. Beibei has published papers to
prestigious conferences and has filed multiple patents. She
received her Ph.D. in computer science from
the University of Massachusetts Lowell. She has a passion
toward natural language processing and data
mining, especially using various tools and techniques to find
hidden patterns and tell stories with data.
Data Science and Big Data Analytics is an exciting domain
where the potential of digital information is
maximized for making intelligent business decisions. We
believe that this is an area that will attract a lot of
talented students and professionals in the short, mid, and long
term.
ffirs.indd 2:43:16:PM/12/11/2014 Page vii
Acknowledgments
EMC Education Services embarked on learning this subject with
the intent to develop an “open” curriculum and
certification. It was a challenging journey at the time as not
many understood what it would take to be a true
data scientist. After initial research (and struggle), we were able
to define what was needed and attract very
16. talented professionals to work on the project. The course, “Data
Science and Big Data Analytics,” has become
well accepted across academia and the industry.
Led by EMC Education Services, this book is the result of
efforts and contributions from a number of key EMC
organizations and supported by the office of the CTO, IT,
Global Services, and Engineering. Many sincere
thanks to many key contributors and subject matter experts
David Dietrich, Barry Heller, and Beibei Yang
for their work developing content and graphics for the chapters.
A special thanks to subject matter experts
John Cardente and Ganesh Rajaratnam for their active
involvement reviewing multiple book chapters and
providing valuable feedback throughout the project.
We are also grateful to the following experts from EMC and
Pivotal for their support in reviewing and improving
the content in this book:
Aidan O’Brien Joe Kambourakis
Alexander Nunes Joe Milardo
Bryan Miletich John Sopka
Dan Baskette Kathryn Stiles
17. Daniel Mepham Ken Taylor
Dave Reiner Lanette Wells
Deborah Stokes Michael Hancock
Ellis Kriesberg Michael Vander Donk
Frank Coleman Narayanan Krishnakumar
Hisham Arafat Richard Moore
Ira Schild Ron Glick
Jack Harwood Stephen Maloney
Jim McGroddy Steve Todd
ffirs.indd 2:43:16:PM/12/11/2014 Page viii
Jody Goncalves Suresh Thankappan
Joe Dery Tom McGowan
We also thank Ira Schild and Shane Goodrich for coordinating
this project, Mallesh Gurram for the cover design, Chris Conroy
and Rob Bradley for graphics, and the publisher, John Wiley
and Sons, for timely support in bringing this book to the
industry.
Nancy Gessler
41. flast.indd 7:23:50:PM/12/12/2014 Page xv
Foreword
Technological advances and the associated changes in practical
daily life have produced a rapidly expanding
“parallel universe” of new content, new data, and new
information sources all around us. Regardless of how one
defines it, the phenomenon of Big Data is ever more present,
ever more pervasive, and ever more important. There
is enormous value potential in Big Data: innovative insights,
improved understanding of problems, and countless
opportunities to predict—and even to shape—the future. Data
Science is the principal means to discover and
tap that potential. Data Science provides ways to deal with and
benefit from Big Data: to see patterns, to discover
relationships, and to make sense of stunningly varied images
and information.
Not everyone has studied statistical analysis at a deep level.
People with advanced degrees in applied math-
ematics are not a commodity. Relatively few organizations have
committed resources to large collections of data
gathered primarily for the purpose of exploratory analysis. And
yet, while applying the practices of Data Science
42. to Big Data is a valuable differentiating strategy at present, it
will be a standard core competency in the not so
distant future.
How does an organization operationalize quickly to take
advantage of this trend? We’ve created this book for
that exact purpose.
EMC Education Services has been listening to the industry and
organizations, observing the multi-faceted
transformation of the technology landscape, and doing direct
research in order to create curriculum and con-
tent to help individuals and organizations transform themselves.
For the domain of Data Science and Big Data
Analytics, our educational strategy balances three things:
people—especially in the context of data science teams,
processes—such as the analytic lifecycle approach presented in
this book, and tools and technologies—in this case
with the emphasis on proven analytic tools.
So let us help you capitalize on this new “parallel universe” that
surrounds us. We invite you to learn about
Data Science and Big Data Analytics through this book and
hope it significantly accelerates your efforts in the
transformational process.
43. flast.indd 7:23:50:PM/12/12/2014 Page xvi
flast.indd 7:23:50:PM/12/12/2014 Page xvii
Introduction
Big Data is creating significant new opportunities for
organizations to derive new value and create competitive
advantage from their most valuable asset: information. For
businesses, Big Data helps drive efficiency, quality, and
personalized products and services, producing improved levels
of customer satisfaction and profit. For scientific
efforts, Big Data analytics enable new avenues of investigation
with potentially richer results and deeper insights
than previously available. In many cases, Big Data analytics
integrate structured and unstructured data with real-
time feeds and queries, opening new paths to innovation and
insight.
This book provides a practitioner’s approach to some of the key
techniques and tools used in Big Data analytics.
Knowledge of these methods will help people become active
contributors to Big Data analytics projects. The book’s
content is designed to assist multiple stakeholders: business and
data analysts looking to add Big Data analytics
44. skills to their portfolio; database professionals and managers of
business intelligence, analytics, or Big Data groups
looking to enrich their analytic skills; and college graduates
investigating data science as a career field.
The content is structured in twelve chapters. The first chapter
introduces the reader to the domain of Big Data,
the drivers for advanced analytics, and the role of the data
scientist. The second chapter presents an analytic project
lifecycle designed for the particular characteristics and
challenges of hypothesis-driven analysis with Big Data.
Chapter 3 examines fundamental statistical techniques in the
context of the open source R analytic software
environment. This chapter also highlights the importance of
exploratory data analysis via visualizations and reviews
the key notions of hypothesis development and testing.
Chapters 4 through 9 discuss a range of advanced analytical
methods, including clustering, classification,
regression analysis, time series and text analysis.
Chapters 10 and 11 focus on specific technologies and tools that
support advanced analytics with Big Data. In
particular, the MapReduce paradigm and its instantiation in the
Hadoop ecosystem, as well as advanced topics
in SQL and in-database text analytics form the focus of these
45. chapters.
XVIII | INTRODUCTION
flast.indd 7:23:50:PM/12/12/2014 Page xviii
Chapter 12 provides guidance on operationalizing Big Data
analytics projects. This chapter focuses on creat-
ing the final deliverables, converting an analytics project to an
ongoing asset of an organization’s operation, and
creating clear, useful visual outputs based on the data.
EMC Academic Alliance
University and college faculties are invited to join the
Academic Alliance program to access unique “open”
curriculum-based education on the following topics:
● Data Science and Big Data Analytics
● Information Storage and Management
● Cloud Infrastructure and Services
● Backup Recovery Systems and Architecture
The program provides faculty with course resources to prepare
students for opportunities that exist in today’s
evolving IT industry at no cost. For more information, visit
http://education.EMC.com/academicalliance.
46. EMC Proven Professional Certification
EMC Proven Professional is a leading education and
certification program in the IT industry, providing compre-
hensive coverage of information storage technologies,
virtualization, cloud computing, data science/Big Data
analytics, and more.
Being proven means investing in yourself and formally
validating your expertise.
This book prepares you for Data Science Associate (EMCDSA)
certification. Visit http://education.EMC
.com for details.
http://education.EMC.com/academicalliance
http://education.EMC
c01.indd 01:58:26:PM 12/09/2014 Page 1
1
Introduction to Big Data
Analytics
Key Concepts
Big Data overview
State of the practice in analytics
Business Intelligence versus Data Science
Key roles for the new Big Data ecosystem
The Data Scientist
47. Examples of Big Data analytics
c01.indd 01:58:26:PM 12/09/2014 Page 2
2 INTRODUCTION TO BIG DATA ANALYTICS
Much has been written about Big Data and the need for
advanced analytics within industry, academia,
and government. Availability of new data sources and the rise
of more complex analytical opportunities
have created a need to rethink existing data architectures to
enable analytics that take advantage of Big
Data. In addition, significant debate exists about what Big Data
is and what kinds of skills are required to
make best use of it. This chapter explains several key concepts
to clarify what is meant by Big Data, why
advanced analytics are needed, how Data Science differs from
Business Intelligence (BI), and what new
roles are needed for the new Big Data ecosystem.
1.1 Big Data Overview
Data is created constantly, and at an ever-increasing rate.
Mobile phones, social media, imaging technologies
to determine a medical diagnosis—all these and more create
new data, and that must be stored somewhere
for some purpose. Devices and sensors automatically generate
48. diagnostic information that needs to be
stored and processed in real time. Merely keeping up with this
huge influx of data is difficult, but substan-
tially more challenging is analyzing vast amounts of it,
especially when it does not conform to traditional
notions of data structure, to identify meaningful patterns and
extract useful information. These challenges
of the data deluge present the opportunity to transform business,
government, science, and everyday life.
Several industries have led the way in developing their ability
to gather and exploit data:
● Credit card companies monitor every purchase their
customers make and can identify fraudulent
purchases with a high degree of accuracy using rules derived by
processing billions of transactions.
● Mobile phone companies analyze subscribers’ calling
patterns to determine, for example, whether a
caller’s frequent contacts are on a rival network. If that rival
network is offering an attractive promo-
tion that might cause the subscriber to defect, the mobile phone
company can proactively offer the
subscriber an incentive to remain in her contract.
● For companies such as LinkedIn and Facebook, data itself is
their primary product. The valuations of
49. these companies are heavily derived from the data they gather
and host, which contains more and
more intrinsic value as the data grows.
Three attributes stand out as defining Big Data characteristics:
● Huge volume of data: Rather than thousands or millions of
rows, Big Data can be billions of rows and
millions of columns.
● Complexity of data types and structures: Big Data reflects
the variety of new data sources, formats,
and structures, including digital traces being left on the web and
other digital repositories for subse-
quent analysis.
● Speed of new data creation and growth: Big Data can
describe high velocity data, with rapid data
ingestion and near real time analysis.
Although the volume of Big Data tends to attract the most
attention, generally the variety and veloc-
ity of the data provide a more apt definition of Big Data. (Big
Data is sometimes described as having 3 Vs:
volume, variety, and velocity.) Due to its size or structure, Big
Data cannot be efficiently analyzed using only
traditional databases or methods. Big Data problems require
50. new tools and technologies to store, manage,
and realize the business benefit. These new tools and
technologies enable creation, manipulation, and
c01.indd 01:58:26:PM 12/09/2014 Page 3
1.1 Big Data Overview 3
management of large datasets and the storage environments that
house them. Another definition of Big
Data comes from the McKinsey Global report from 2011:
Big Data is data whose scale, distribution, diversity, and/or
timeliness require the
use of new technical architectures and analytics to enable
insights that unlock new
sources of business value.
McKinsey & Co.; Big Data: The Next Frontier for Innovation,
Competition, and
Productivity [1]
McKinsey’s definition of Big Data implies that organizations
will need new data architectures and ana-
lytic sandboxes, new tools, new analytical methods, and an
integration of multiple skills into the new role
of the data scientist, which will be discussed in Section 1.3.
51. Figure 1-1 highlights several sources of the Big
Data deluge.
FIGURE 1-1 What’s driving the data deluge
The rate of data creation is accelerating, driven by many of the
items in Figure 1-1.
Social media and genetic sequencing are among the fastest-
growing sources of Big Data and examples
of untraditional sources of data being used for analysis.
For example, in 2012 Facebook users posted 700 status updates
per second worldwide, which can be
leveraged to deduce latent interests or political views of users
and show relevant ads. For instance, an
update in which a woman changes her relationship status from
“single” to “engaged” would trigger ads
on bridal dresses, wedding planning, or name-changing services.
Facebook can also construct social graphs to analyze which
users are connected to each other as an
interconnected network. In March 2013, Facebook released a
new feature called “Graph Search,” enabling
users and developers to search social graphs for people with
similar interests, hobbies, and shared locations.
52. c01.indd 01:58:26:PM 12/09/2014 Page 4
4 INTRODUCTION TO BIG DATA ANALYTICS
Another example comes from genomics. Genetic sequencing and
human genome mapping provide a
detailed understanding of genetic makeup and lineage. The
health care industry is looking toward these
advances to help predict which illnesses a person is likely to get
in his lifetime and take steps to avoid these
maladies or reduce their impact through the use of personalized
medicine and treatment. Such tests also
highlight typical responses to different medications and
pharmaceutical drugs, heightening risk awareness
of specific drug treatments.
While data has grown, the cost to perform this work has fallen
dramatically. The cost to sequence one
human genome has fallen from $100 million in 2001 to $10,000
in 2011, and the cost continues to drop. Now,
websites such as 23andme (Figure 1-2) offer genotyping for less
than $100. Although genotyping analyzes
only a fraction of a genome and does not provide as much
granularity as genetic sequencing, it does point
to the fact that data and complex analysis is becoming more
prevalent and less expensive to deploy.
53. FIGURE 1-2 Examples of what can be learned through
genotyping, from 23andme.com
c01.indd 01:58:26:PM 12/09/2014 Page 5
1.1 Big Data Overview 5
As illustrated by the examples of social media and genetic
sequencing, individuals and organizations
both derive benefits from analysis of ever-larger and more
complex datasets that require increasingly
powerful analytical capabilities.
1.1.1 Data Structures
Big data can come in multiple forms, including structured and
non-structured data such as financial
data, text files, multimedia files, and genetic mappings.
Contrary to much of the traditional data analysis
performed by organizations, most of the Big Data is
unstructured or semi-structured in nature, which
requires different techniques and tools to process and analyze.
[2] Distributed computing environments
and massively parallel processing (MPP) architectures that
enable parallelized data ingest and analysis are
the preferred approach to process such complex data.
With this in mind, this section takes a closer look at data
54. structures.
Figure 1-3 shows four types of data structures, with 80–90% of
future data growth coming from non-
structured data types. [2] Though different, the four are
commonly mixed. For example, a classic Relational
Database Management System (RDBMS) may store call logs for
a software support call center. The RDBMS
may store characteristics of the support calls as typical
structured data, with attributes such as time stamps,
machine type, problem type, and operating system. In addition,
the system will likely have unstructured,
quasi- or semi-structured data, such as free-form call log
information taken from an e-mail ticket of the
problem, customer chat history, or transcript of a phone call
describing the technical problem and the solu-
tion or audio file of the phone call conversation. Many insights
could be extracted from the unstructured,
quasi- or semi-structured data in the call center data.
FIGURE 1-3 Big Data Growth is increasingly unstructured
c01.indd 02:4:36:PM 12/09/2014 Page 6
6 INTRODUCTION TO BIG DATA ANALYTICS
55. Although analyzing structured data tends to be the most familiar
technique, a different technique is
required to meet the challenges to analyze semi-structured data
(shown as XML), quasi-structured (shown
as a clickstream), and unstructured data.
Here are examples of how each of the four main types of data
structures may look.
● Structured data: Data containing a defined data type, format,
and structure (that is, transaction data,
online analytical processing [OLAP] data cubes, traditional
RDBMS, CSV files, and even simple spread-
sheets). See Figure 1-4.
FIGURE 1-4 Example of structured data
● Semi-structured data: Textual data files with a discernible
pattern that enables parsing (such
as Extensible Markup Language [XML] data files that are self-
describing and defined by an XML
schema). See Figure 1-5.
● Quasi-structured data: Textual data with erratic data formats
that can be formatted with effort,
tools, and time (for instance, web clickstream data that may
contain inconsistencies in data values
and formats). See Figure 1-6.
56. ● Unstructured data: Data that has no inherent structure, which
may include text documents, PDFs,
images, and video. See Figure 1-7.
c01.indd 02:4:36:PM 12/09/2014 Page 7
1.1 Big Data Overview 7
Quasi-structured data is a common phenomenon that bears
closer scrutiny. Consider the following
example. A user attends the EMC World conference and
subsequently runs a Google search online to find
information related to EMC and Data Science. This would
produce a URL such as https://www.google
.com/#q=EMC+ data+science and a list of results, such as in the
first graphic of Figure 1-5.
FIGURE 1-5 Example of semi-structured data
After doing this search, the user may choose the second link, to
read more about the headline “Data
Scientist—EMC Education, Training, and Certification.” This
brings the user to an emc.com site focused on
this topic and a new URL,
https://education.emc.com/guest/campaign/data_science
https://www.google
https://education.emc.com/guest/campaign/data_science
57. c01.indd 02:4:36:PM 12/09/2014 Page 8
8 INTRODUCTION TO BIG DATA ANALYTICS
.aspx, that displays the page shown as (2) in Figure 1-6.
Arriving at this site, the user may decide to click
to learn more about the process of becoming certified in data
science. The user chooses a link toward the
top of the page on Certifications, bringing the user to a new
URL: https://education.emc.com/
guest/certification/framework/stf/data_science.aspx, which is
(3) in Figure 1-6.
Visiting these three websites adds three URLs to the log files
monitoring the user’s computer or network
use. These three URLs are:
https://www.google.com/#q=EMC+data+science
https://education.emc.com/guest/campaign/data_science.aspx
https://education.emc.com/guest/certification/framework/stf/dat
a_
science.aspx
FIGURE 1-6 Example of EMC Data Science search results
https://education.emc.com
https://www.google.com/#q=EMC+data+science
https://education.emc.com/guest/campaign/data_science.aspx
https://education.emc.com/guest/certification/framework/stf/dat
a_
c01.indd 02:4:36:PM 12/09/2014 Page 9
58. 1.1 Big Data Overview 9
FIGURE 1-7 Example of unstructured data: video about
Antarctica expedition [3]
This set of three URLs reflects the websites and actions taken to
find Data Science information related
to EMC. Together, this comprises a clickstream that can be
parsed and mined by data scientists to discover
usage patterns and uncover relationships among clicks and areas
of interest on a website or group of sites.
The four data types described in this chapter are sometimes
generalized into two groups: structured
and unstructured data. Big Data describes new kinds of data
with which most organizations may not be
used to working. With this in mind, the next section discusses
common technology architectures from the
standpoint of someone wanting to analyze Big Data.
1.1.2 Analyst Perspective on Data Repositories
The introduction of spreadsheets enabled business users to
create simple logic on data structured in rows
and columns and create their own analyses of business
problems. Database administrator training is not
required to create spreadsheets: They can be set up to do many
things quickly and independently of
59. information technology (IT) groups. Spreadsheets are easy to
share, and end users have control over the
logic involved. However, their proliferation can result in “many
versions of the truth.” In other words, it
can be challenging to determine if a particular user has the most
relevant version of a spreadsheet, with
the most current data and logic in it. Moreover, if a laptop is
lost or a file becomes corrupted, the data and
logic within the spreadsheet could be lost. This is an ongoing
challenge because spreadsheet programs
such as Microsoft Excel still run on many computers worldwide.
With the proliferation of data islands (or
spreadmarts), the need to centralize the data is more pressing
than ever.
As data needs grew, so did more scalable data warehousing
solutions. These technologies enabled
data to be managed centrally, providing benefits of security,
failover, and a single repository where users
c01.indd 02:4:36:PM 12/09/2014 Page 10
10 INTRODUCTION TO BIG DATA ANALYTICS
could rely on getting an “official” source of data for financial
reporting or other mission-critical tasks. This
60. structure also enabled the creation of OLAP cubes and BI
analytical tools, which provided quick access to a
set of dimensions within an RDBMS. More advanced features
enabled performance of in-depth analytical
techniques such as regressions and neural networks. Enterprise
Data Warehouses (EDWs) are critical for
reporting and BI tasks and solve many of the problems that
proliferating spreadsheets introduce, such as
which of multiple versions of a spreadsheet is correct. EDWs—
and a good BI strategy—provide direct data
feeds from sources that are centrally managed, backed up, and
secured.
Despite the benefits of EDWs and BI, these systems tend to
restrict the flexibility needed to perform
robust or exploratory data analysis. With the EDW model, data
is managed and controlled by IT groups
and database administrators (DBAs), and data analysts must
depend on IT for access and changes to the
data schemas. This imposes longer lead times for analysts to get
data; most of the time is spent waiting for
approvals rather than starting meaningful work. Additionally,
many times the EDW rules restrict analysts
from building datasets. Consequently, it is common for
additional systems to emerge containing critical
61. data for constructing analytic datasets, managed locally by
power users. IT groups generally dislike exis-
tence of data sources outside of their control because, unlike an
EDW, these datasets are not managed,
secured, or backed up. From an analyst perspective, EDW and
BI solve problems related to data accuracy
and availability. However, EDW and BI introduce new problems
related to flexibility and agility, which were
less pronounced when dealing with spreadsheets.
A solution to this problem is the analytic sandbox, which
attempts to resolve the conflict for analysts and
data scientists with EDW and more formally managed corporate
data. In this model, the IT group may still
manage the analytic sandboxes, but they will be purposefully
designed to enable robust analytics, while
being centrally managed and secured. These sandboxes, often
referred to as workspaces, are designed to
enable teams to explore many datasets in a controlled fashion
and are not typically used for enterprise-
level financial reporting and sales dashboards.
Many times, analytic sandboxes enable high-performance
computing using in-database processing—
the analytics occur within the database itself. The idea is that
performance of the analysis will be better if
62. the analytics are run in the database itself, rather than bringing
the data to an analytical tool that resides
somewhere else. In-database analytics, discussed further in
Chapter 11, “Advanced Analytics—Technology
and Tools: In-Database Analytics,” creates relationships to
multiple data sources within an organization and
saves time spent creating these data feeds on an individual
basis. In-database processing for deep analytics
enables faster turnaround time for developing and executing
new analytic models, while reducing, though
not eliminating, the cost associated with data stored in local,
“shadow” file systems. In addition, rather
than the typical structured data in the EDW, analytic sandboxes
can house a greater variety of data, such
as raw data, textual data, and other kinds of unstructured data,
without interfering with critical production
databases. Table 1-1 summarizes the characteristics of the data
repositories mentioned in this section.
TABLE 1-1 Types of Data Repositories, from an Analyst
Perspective
Data Repository Characteristics
Spreadsheets and
data marts
63. (“spreadmarts”)
Spreadsheets and low-volume databases for recordkeeping
Analyst depends on data extracts.
c01.indd 02:4:36:PM 12/09/2014 Page 11
1.2 State of the Practice in Analytics 11
Data Warehouses Centralized data containers in a purpose-built
space
Supports BI and reporting, but restricts robust analyses
Analyst dependent on IT and DBAs for data access and schema
changes
Analysts must spend significant time to get aggregated and
disaggre-
gated data extracts from multiple sources.
Analytic Sandbox
(workspaces)
Data assets gathered from multiple sources and technologies for
analysis
Enables flexible, high-performance analysis in a nonproduction
environ-
64. ment; can leverage in-database processing
Reduces costs and risks associated with data replication into
“shadow” file
systems
“Analyst owned” rather than “DBA owned”
There are several things to consider with Big Data Analytics
projects to ensure the approach fits with
the desired goals. Due to the characteristics of Big Data, these
projects lend themselves to decision sup-
port for high-value, strategic decision making with high
processing complexity. The analytic techniques
used in this context need to be iterative and flexible, due to the
high volume of data and its complexity.
Performing rapid and complex analysis requires high throughput
network connections and a consideration
for the acceptable amount of latency. For instance, developing a
real-time product recommender for a
website imposes greater system demands than developing a
near-real-time recommender, which may
still provide acceptable performance, have slightly greater
latency, and may be cheaper to deploy. These
considerations require a different approach to thinking about
analytics challenges, which will be explored
65. further in the next section.
1.2 State of the Practice in Analytics
Current business problems provide many opportunities for
organizations to become more analytical and
data driven, as shown in Table 1-2.
TABLE 1-2 Business Drivers for Advanced Analytics
Business Driver Examples
Optimize business operations Sales, pricing, profitability,
efficiency
Identify business risk Customer churn, fraud, default
Predict new business opportunities Upsell, cross-sell, best new
customer prospects
Comply with laws or regulatory
requirements
Anti-Money Laundering, Fair Lending, Basel II-III, Sarbanes-
Oxley (SOX)
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12 INTRODUCTION TO BIG DATA ANALYTICS
Table 1-2 outlines four categories of common business problems
that organizations contend with where
66. they have an opportunity to leverage advanced analytics to
create competitive advantage. Rather than only
performing standard reporting on these areas, organizations can
apply advanced analytical techniques
to optimize processes and derive more value from these common
tasks. The first three examples do not
represent new problems. Organizations have been trying to
reduce customer churn, increase sales, and
cross-sell customers for many years. What is new is the
opportunity to fuse advanced analytical techniques
with Big Data to produce more impactful analyses for these
traditional problems. The last example por-
trays emerging regulatory requirements. Many compliance and
regulatory laws have been in existence for
decades, but additional requirements are added every year,
which represent additional complexity and
data requirements for organizations. Laws related to anti-money
laundering (AML) and fraud prevention
require advanced analytical techniques to comply with and
manage properly.
1.2.1 BI Versus Data Science
The four business drivers shown in Table 1-2 require a variety
of analytical techniques to address them prop-
erly. Although much is written generally about analytics, it is
67. important to distinguish between BI and Data
Science. As shown in Figure 1-8, there are several ways to
compare these groups of analytical techniques.
One way to evaluate the type of analysis being performed is to
examine the time horizon and the kind
of analytical approaches being used. BI tends to provide reports,
dashboards, and queries on business
questions for the current period or in the past. BI systems make
it easy to answer questions related to
quarter-to-date revenue, progress toward quarterly targets, and
understand how much of a given product
was sold in a prior quarter or year. These questions tend to be
closed-ended and explain current or past
behavior, typically by aggregating historical data and grouping
it in some way. BI provides hindsight and
some insight and generally answers questions related to “when”
and “where” events occurred.
By comparison, Data Science tends to use disaggregated data in
a more forward-looking, exploratory
way, focusing on analyzing the present and enabling informed
decisions about the future. Rather than
aggregating historical data to look at how many of a given
product sold in the previous quarter, a team
may employ Data Science techniques such as time series
68. analysis, further discussed in Chapter 8, “Advanced
Analytical Theory and Methods: Time Series Analysis,” to
forecast future product sales and revenue more
accurately than extending a simple trend line. In addition, Data
Science tends to be more exploratory in
nature and may use scenario optimization to deal with more
open-ended questions. This approach provides
insight into current activity and foresight into future events,
while generally focusing on questions related
to “how” and “why” events occur.
Where BI problems tend to require highly structured data
organized in rows and columns for accurate
reporting, Data Science projects tend to use many types of data
sources, including large or unconventional
datasets. Depending on an organization’s goals, it may choose
to embark on a BI project if it is doing reporting,
creating dashboards, or performing simple visualizations, or it
may choose Data Science projects if it needs
to do a more sophisticated analysis with disaggregated or varied
datasets.
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1.2 State of the Practice in Analytics 13
69. FIGURE 1-8 Comparing BI with Data Science
1.2.2 Current Analytical Architecture
As described earlier, Data Science projects need workspaces
that are purpose-built for experimenting with
data, with flexible and agile data architectures. Most
organizations still have data warehouses that provide
excellent support for traditional reporting and simple data
analysis activities but unfortunately have a more
difficult time supporting more robust analyses. This section
examines a typical analytical data architecture
that may exist within an organization.
Figure 1-9 shows a typical data architecture and several of the
challenges it presents to data scientists
and others trying to do advanced analytics. This section
examines the data flow to the Data Scientist and
how this individual fits into the process of getting data to
analyze on projects.
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14 INTRODUCTION TO BIG DATA ANALYTICS
FIGURE 1-9 Typical analytic architecture
1. For data sources to be loaded into the data warehouse, data
70. needs to be well understood,
structured, and normalized with the appropriate data type
definitions. Although this kind of
centralization enables security, backup, and failover of highly
critical data, it also means that data
typically must go through significant preprocessing and
checkpoints before it can enter this sort
of controlled environment, which does not lend itself to data
exploration and iterative analytics.
2. As a result of this level of control on the EDW, additional
local systems may emerge in the form of
departmental warehouses and local data marts that business
users create to accommodate their
need for flexible analysis. These local data marts may not have
the same constraints for secu-
rity and structure as the main EDW and allow users to do some
level of more in-depth analysis.
However, these one-off systems reside in isolation, often are not
synchronized or integrated with
other data stores, and may not be backed up.
3. Once in the data warehouse, data is read by additional
applications across the enterprise for BI
and reporting purposes. These are high-priority operational
processes getting critical data feeds
71. from the data warehouses and repositories.
4. At the end of this workflow, analysts get data provisioned
for their downstream analytics.
Because users generally are not allowed to run custom or
intensive analytics on production
databases, analysts create data extracts from the EDW to
analyze data offline in R or other local
analytical tools. Many times these tools are limited to in-
memory analytics on desktops analyz-
ing samples of data, rather than the entire population of a
dataset. Because these analyses are
based on data extracts, they reside in a separate location, and
the results of the analysis—and
any insights on the quality of the data or anomalies—rarely are
fed back into the main data
repository.
Because new data sources slowly accumulate in the EDW due to
the rigorous validation and
data structuring process, data is slow to move into the EDW,
and the data schema is slow to change.
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72. 1.2 State of the Practice in Analytics 15
Departmental data warehouses may have been originally
designed for a specific purpose and set of business
needs, but over time evolved to house more and more data,
some of which may be forced into existing
schemas to enable BI and the creation of OLAP cubes for
analysis and reporting. Although the EDW achieves
the objective of reporting and sometimes the creation of
dashboards, EDWs generally limit the ability of
analysts to iterate on the data in a separate nonproduction
environment where they can conduct in-depth
analytics or perform analysis on unstructured data.
The typical data architectures just described are designed for
storing and processing mission-critical
data, supporting enterprise applications, and enabling corporate
reporting activities. Although reports and
dashboards are still important for organizations, most
traditional data architectures inhibit data exploration
and more sophisticated analysis. Moreover, traditional data
architectures have several additional implica-
tions for data scientists.
● High-value data is hard to reach and leverage, and predictive
analytics and data mining activities
73. are last in line for data. Because the EDWs are designed for
central data management and reporting,
those wanting data for analysis are generally prioritized after
operational processes.
● Data moves in batches from EDW to local analytical tools.
This workflow means that data scientists
are limited to performing in-memory analytics (such as with R,
SAS, SPSS, or Excel), which will restrict
the size of the datasets they can use. As such, analysis may be
subject to constraints of sampling,
which can skew model accuracy.
● Data Science projects will remain isolated and ad hoc, rather
than centrally managed. The implica-
tion of this isolation is that the organization can never harness
the power of advanced analytics in a
scalable way, and Data Science projects will exist as
nonstandard initiatives, which are frequently not
aligned with corporate business goals or strategy.
All these symptoms of the traditional data architecture result in
a slow “time-to-insight” and lower
business impact than could be achieved if the data were more
readily accessible and supported by an envi-
ronment that promoted advanced analytics. As stated earlier,
one solution to this problem is to introduce
74. analytic sandboxes to enable data scientists to perform
advanced analytics in a controlled and sanctioned
way. Meanwhile, the current Data Warehousing solutions
continue offering reporting and BI services to
support management and mission-critical operations.
1.2.3 Drivers of Big Data
To better understand the market drivers related to Big Data, it is
helpful to first understand some past
history of data stores and the kinds of repositories and tools to
manage these data stores.
As shown in Figure 1-10, in the 1990s the volume of
information was often measured in terabytes.
Most organizations analyzed structured data in rows and
columns and used relational databases and data
warehouses to manage large stores of enterprise information.
The following decade saw a proliferation of
different kinds of data sources—mainly productivity and
publishing tools such as content management
repositories and networked attached storage systems—to
manage this kind of information, and the data
began to increase in size and started to be measured at petabyte
scales. In the 2010s, the information that
organizations try to manage has broadened to include many
other kinds of data. In this era, everyone
75. and everything is leaving a digital footprint. Figure 1-10 shows
a summary perspective on sources of Big
Data generated by new applications and the scale and growth
rate of the data. These applications, which
generate data volumes that can be measured in exabyte scale,
provide opportunities for new analytics and
driving new value for organizations. The data now comes from
multiple sources, such as these:
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16 INTRODUCTION TO BIG DATA ANALYTICS
● Medical information, such as genomic sequencing and
diagnostic imaging
● Photos and video footage uploaded to the World Wide Web
● Video surveillance, such as the thousands of video cameras
spread across a city
● Mobile devices, which provide geospatial location data of the
users, as well as metadata about text
messages, phone calls, and application usage on smart phones
● Smart devices, which provide sensor-based collection of
information from smart electric grids, smart
buildings, and many other public and industry infrastructures
76. ● Nontraditional IT devices, including the use of radio-
frequency identification (RFID) readers, GPS
navigation systems, and seismic processing
FIGURE 1-10 Data evolution and the rise of Big Data sources
The Big Data trend is generating an enormous amount of
information from many new sources. This
data deluge requires advanced analytics and new market players
to take advantage of these opportunities
and new market dynamics, which will be discussed in the
following section.
1.2.4 Emerging Big Data Ecosystem and a New Approach to
Analytics
Organizations and data collectors are realizing that the data they
can gather from individuals contains
intrinsic value and, as a result, a new economy is emerging. As
this new digital economy continues to
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1.2 State of the Practice in Analytics 17
evolve, the market sees the introduction of data vendors and
data cleaners that use crowdsourcing (such
as Mechanical Turk and GalaxyZoo) to test the outcomes of
machine learning techniques. Other vendors
77. offer added value by repackaging open source tools in a simpler
way and bringing the tools to market.
Vendors such as Cloudera, Hortonworks, and Pivotal have
provided this value-add for the open source
framework Hadoop.
As the new ecosystem takes shape, there are four main groups
of players within this interconnected
web. These are shown in Figure 1-11.
● Data devices [shown in the (1) section of Figure 1-11] and
the “Sensornet” gather data from multiple
locations and continuously generate new data about this data.
For each gigabyte of new data cre-
ated, an additional petabyte of data is created about that data.
[2]
● For example, consider someone playing an online video game
through a PC, game console,
or smartphone. In this case, the video game provider captures
data about the skill and levels
attained by the player. Intelligent systems monitor and log how
and when the user plays the
game. As a consequence, the game provider can fine-tune the
difficulty of the game,
suggest other related games that would most likely interest the
78. user, and offer additional
equipment and enhancements for the character based on the
user’s age, gender, and
interests. This information may get stored locally or uploaded to
the game provider’s cloud
to analyze the gaming habits and opportunities for upsell and
cross-sell, and identify
archetypical profiles of specific kinds of users.
● Smartphones provide another rich source of data. In addition
to messaging and basic phone
usage, they store and transmit data about Internet usage, SMS
usage, and real-time location.
This metadata can be used for analyzing traffic patterns by
scanning the density of smart-
phones in locations to track the speed of cars or the relative
traffic congestion on busy
roads. In this way, GPS devices in cars can give drivers real-
time updates and offer alternative
routes to avoid traffic delays.
● Retail shopping loyalty cards record not just the amount an
individual spends, but the loca-
tions of stores that person visits, the kinds of products
purchased, the stores where goods
79. are purchased most often, and the combinations of products
purchased together. Collecting
this data provides insights into shopping and travel habits and
the likelihood of successful
advertisement targeting for certain types of retail promotions.
● Data collectors [the blue ovals, identified as (2) within
Figure 1-11] include sample entities that
collect data from the device and users.
● Data results from a cable TV provider tracking the shows a
person watches, which TV
channels someone will and will not pay for to watch on
demand, and the prices someone is
willing to pay for premium TV content
● Retail stores tracking the path a customer takes through their
store while pushing a shop-
ping cart with an RFID chip so they can gauge which products
get the most foot traffic using
geospatial data collected from the RFID chips
● Data aggregators (the dark gray ovals in Figure 1-11, marked
as (3)) make sense of the data collected
from the various entities from the “SensorNet” or the “Internet
of Things.” These organizations
compile data from the devices and usage patterns collected by
80. government agencies, retail stores,
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18 INTRODUCTION TO BIG DATA ANALYTICS
and websites. In turn, they can choose to transform and package
the data as products to sell to list
brokers, who may want to generate marketing lists of people
who may be good targets for specific ad
campaigns.
● Data users and buyers are denoted by (4) in Figure 1-11.
These groups directly benefit from the data
collected and aggregated by others within the data value chain.
● Retail banks, acting as a data buyer, may want to know which
customers have the highest
likelihood to apply for a second mortgage or a home equity line
of credit. To provide input
for this analysis, retail banks may purchase data from a data
aggregator. This kind of data
may include demographic information about people living in
specific locations; people who
appear to have a specific level of debt, yet still have solid credit
scores (or other characteris-
81. tics such as paying bills on time and having savings accounts)
that can be used to infer credit
worthiness; and those who are searching the web for
information about paying off debts or
doing home remodeling projects. Obtaining data from these
various sources and aggrega-
tors will enable a more targeted marketing campaign, which
would have been more chal-
lenging before Big Data due to the lack of information or high-
performing technologies.
● Using technologies such as Hadoop to perform natural
language processing on
unstructured, textual data from social media websites, users can
gauge the reaction to
events such as presidential campaigns. People may, for
example, want to determine public
sentiments toward a candidate by analyzing related blogs and
online comments. Similarly,
data users may want to track and prepare for natural disasters by
identifying which areas
a hurricane affects first and how it moves, based on which
geographic areas are tweeting
about it or discussing it via social media.
FIGURE 1-11 Emerging Big Data ecosystem
82. c01.indd 02:4:36:PM 12/09/2014 Page 19
1.3 Key Roles for the New Big Data Ecosystem 19
As illustrated by this emerging Big Data ecosystem, the kinds of
data and the related market dynamics
vary greatly. These datasets can include sensor data, text,
structured datasets, and social media. With this
in mind, it is worth recalling that these datasets will not work
well within traditional EDWs, which were
architected to streamline reporting and dashboards and be
centrally managed. Instead, Big Data problems
and projects require different approaches to succeed.
Analysts need to partner with IT and DBAs to get the data they
need within an analytic sandbox. A
typical analytical sandbox contains raw data, aggregated data,
and data with multiple kinds of structure.
The sandbox enables robust exploration of data and requires a
savvy user to leverage and take advantage
of data in the sandbox environment.
1.3 Key Roles for the New Big Data Ecosystem
As explained in the context of the Big Data ecosystem in
Section 1.2.4, new players have emerged to curate,