Final Assignment Written assignment (Research Proposal) Activity brief BRM221 – Research Methods II Online campus Professor: Dr. Hasan Evrim Arici | [email protected] Description Research Proposal The students will develop a research proposal for their future dissertation. Please use the “Dissertation Proposal Form” attached. Format This activity must meet the following formatting requirements: • Font size 12 • Double-spaced • Word Limit: N/A • Harvard Referencing System Goal(s) • To evaluate students’ knowledge of the theory and practice of quantitative research methods. • To evaluate the students on how to formulate, analyze, and present their research findings. • To appraise students’ knowledge about research philosophies, and how to apply them effectively in their research; • To evaluate how students choose the appropriate research designs/methods; • To evaluate students’ understanding of the various ethical considerations while conducting and presenting their research. Due date Date: Monday, 20th September 2021 Time: 14.00h CEST Weight towards final grade This activity has a weight of 60% towards the final grade. Learning outcomes • Understand: the different philosophies of research which act as a guide and filter to formulating appropriate research designs. • Knowledge: acquire knowledge of the different research approaches; techniques and methods. • Identify: which data collection method(s) best correlate to their research. • Apply: research methods skills developed in this course will be applied to any research conducted by the student. • Analyze and Evaluate: the results of their research findings as a basis and context for real world business decision making. Assessment criteria The grading rubric below will be used to evaluate students’ assignment. Good luck! Rubric: written assignment Criteria Accomplished (A) Proficient (B) Partially proficient (C) Borderline (D) Fail (F) Problem identification The business issue has been correctly identified, with a competent and comprehensive explanation of key driving forces and considerations. Impact on company operations has been correctly identified. Thorough analysis of the issue is presented. The student correctly identified the issue(s), taking into account a variety of environmental and contextual drivers. Key case information has been identified and analyzed. The student correctly identified the case (issues), considering obvious environmental/contextual drivers. There is evidence of analysis, but it lacks depth. The student correctly identified the issue(s) but analysis was weak. An absence of context – the work is basically descriptive with little analysis. The student failed to correctly identify the issue(s); analysis was incorrect or too superficial to be of use; information was misinterpreted. Information gathering The student showed skill in gathe ...

1. Final Assignment
Written assignment (Research Proposal)
Activity brief
BRM221 – Research Methods II
Online campus
Professor: Dr. Hasan Evrim Arici | [email protected]
Description Research Proposal
The students will develop a research proposal for their future
dissertation.
Please use the “Dissertation Proposal Form” attached.
Format This activity must meet the following
formatting requirements:
• Font size 12
• Double-spaced
• Word Limit: N/A
• Harvard Referencing System
Goal(s) • To evaluate students’ knowledge of the theory and
practice of
quantitative research methods.

2. • To evaluate the students on how to formulate, analyze, and
present their research findings.
• To appraise students’ knowledge about research philosophies,
and how to apply them effectively in their research;
• To evaluate how students choose the appropriate research
designs/methods;
• To evaluate students’ understanding of the various ethical
considerations while conducting and presenting their research.
Due date Date: Monday, 20th September 2021
Time: 14.00h CEST
Weight towards
final grade
This activity has a weight of 60%
towards the final grade.
Learning
outcomes
• Understand: the different philosophies of research which act
as a
guide and filter to formulating appropriate research designs.
• Knowledge: acquire knowledge of the different research
approaches; techniques and methods.
• Identify: which data collection method(s) best correlate to
their
research.

3. • Apply: research methods skills developed in this course will
be
applied to any research conducted by the student.
• Analyze and Evaluate: the results of their research findings as
a
basis and context for real world business decision making.
Assessment
criteria
The grading rubric below will be used to
evaluate students’ assignment.
Good luck!
Rubric: written assignment
Criteria Accomplished (A) Proficient (B) Partially proficient
(C) Borderline (D) Fail (F)
Problem
identification
The business issue has been
correctly identified, with a
competent and comprehensive
explanation of key driving
forces and considerations.
Impact on company operations
has been correctly identified.

4. Thorough analysis of the issue
is presented.
The student correctly identified
the issue(s), taking into account
a variety of environmental and
contextual drivers. Key case
information has been identified
and analyzed.
The student correctly identified
the case (issues), considering
obvious
environmental/contextual
drivers. There is evidence of
analysis, but it lacks depth.
The student correctly identified
the issue(s) but analysis was
weak. An absence of context –
the work is basically descriptive
with little analysis.
The student failed to correctly
identify the issue(s); analysis
was incorrect or too superficial
to be of use; information was
misinterpreted.
Information
gathering
The student showed skill in
gathering information and
analyzing it for the purposes of
filling the information gaps

5. identified. Comprehensive and
relevant.
Relevant information gaps were
identified and additional
relevant information was found
to fill them. At least two different
types of sources were used.
The student demonstrates
coherent criteria for selecting
information but needs greater
depth.
The student correctly identified
at least one information gap
and found relevant information,
but which was limited in scope.
Some evidence of sound
criteria for selecting information
but not consistent throughout.
Needs expansion.
An information gap was
identified and the student found
additional information to fill it.
However, this was limited in
scope. Weak criteria for the
selection of necessary
information.
Information was taken at face
value with no questioning of its
relevance or value. Gaps in the
information were not identified
or were incorrect.

6. Conclusions The student evaluated,
analyzed, synthesized all
information provided to create a
perceptive set of conclusions to
support the decisions and
solutions.
The student evaluated,
analyzed and synthesized to
create a conclusion(s) which
support decisions and
solutions.
The student reached
conclusions, but they were
limited and provided minimal
direction for decision-making
and solutions.
The conclusion was reasonable
but lacked depth and would not
be a basis for suitable strategy
development.
The student formed a
conclusion, but it was not
reasonable. It was either
unjustified, incorrect or
unrelated to the case in hand.
Solution

7. s The student used problem
solving techniques to make
thoughtful, justified decisions
about difficult and conflicting
issues. A realistic solution was
chosen which would provide
maximum benefit to the
company. Alternative solutions
were explored and ruled out.
The student used problem
solving techniques to make
appropriate decisions about
complex issues. Relevant
questions were asked and
answered. A realistic solution
was chosen. Alternatives were
identified, explored and ruled
out.
The student used problem-
solving techniques to make
appropriate decisions about
simpler issues. The solution
has limited benefit but does

8. show understanding of
implications of the decision.
Alternatives were mentioned
but not explored.
The student used problem
solving techniques to make
decisions about simpler issues
but disregarded more complex
issues. Implications of the
decision were not considered.
Alternatives were not offered.
The student formed a
conclusion, but it was not
reasonable. It was either
unjustified, incorrect or
unrelated to the case in hand.
Dissertation Proposal Form

9. Student Name:
Program:
I. Proposed Dissertation Title: The title (tentative) should be
precise to allow the reader to
comprehend the subject matter of the work.
Click or tap here to enter text.
II. Research Question or Hypothesis: State clearly what your
research interest is. Define your
research question/hypothesis and the main objectives of your
research (Min 300 words).
Click or tap here to enter text.
III. Review of Literature/Background: Make a synthesis of the
contributions made in your
research field by accredited scholars. Describe how your
intended research will complement and
expand on the current literature, and what contributions you
intend to make to the existing knowledge
(Min 800 words).

10. Note: Should you opt for a Business Plan, then provide a full
analysis of the business conditions.
Click or tap here to enter text.
IV. Research Methodology: Clearly indicate the methods and
techniques which you are planning
to use to gather information and investigate the identified
problem. (Min 800 words).
Click or tap here to enter text.
V. Selected Bibliography: Please indicate a representative list
of the main bibliographical
sources you intend to utilize for your dissertation. Please
provide full citations. (Min 20 sources)
Click or tap here to enter text.
VI. Research and Writing Timeline: Indicate your expected
research timetable: starting date,
research time, data analysis time, writing time, editing time,
date of first draft submission, expected
defense time. You may use a Gantt chart. (Min 100 words.)

11. Click or tap here to enter text.
VII. Ethics: How does your research relate to the ethical aspects
of your subject matter? (Min
100 words.)
Click or tap here to enter text.
DATA4200
Data Acquisition and

12. Management
Lesson 2
Relational Database Design: Data
Storage, pre-processing, querying
and Maintenance
Copyright Notice
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WARNING
This material has been reproduced and communicated to you by
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Education pursuant to Part VB of the Copyright Act 1968 (the

13. Act). The material in
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Any further reproduction
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Do not remove this notice
2
Lesson Learning Outcomes
1 Examine data storage options
2 Investigate traditional relational database
design
3 Define data pre-processing
4 Assess data pre-processing options

14. 5 Create SQL search commands in
preparation for the hands-on workshops
This Week’s Big Idea
“Data that is loved tends to survive.”
– Kurt Bollacker, computer scientist.
This Photo by Unknown Author is licensed under CC BY
https://www.linkedin.com/in/kurt-bollacker-997b851/
https://www.flickr.com/photos/bixentro/2157792847
https://creativecommons.org/licenses/by/3.0/
Software Choices for SQL
• See week 1 webinar recording by Santos (if you haven’t
already) on how to install a version of SQL
• Choices

15. – Macs and low grade PCs, Azure Data Studio
– https://docs.microsoft.com/en-us/sql/azure-data-
studio/download-azure-data-studio?view=sql-server-ver15
– Or for other PCs, Microsoft SQL management server
– https://docs.microsoft.com/en-us/sql/ssms/download-sql-
server-
management-studio-ssms?view=sql-server-ver15
– Don’t forget Power BI too
https://docs.microsoft.com/en-us/sql/azure-data-
studio/download-azure-data-studio?view=sql-server-ver15
https://docs.microsoft.com/en-us/sql/ssms/download-sql-server-
management-studio-ssms?view=sql-server-ver15
Approaches to Data Storage
• In this workshop we will compare old and new
ways of storing, cleaning and querying data

16. • Note: There are many data storage architectures
old and new.
https://www.juku.it/year-enterprise-object-storage-quick-
product-roundup-part-2/
https://www.juku.it/year-enterprise-object-storage-quick-
product-roundup-part-2/
Storage of Data (p1)
• Data Lake
– Repository for large amounts of raw data from multiple
sources and in
many formats, some of which may not be useful
• Data hub
– Collection of raw data organised for sharing.
– The data is physically moved and re-indexed (harmonised)
into a new

17. system.
• Data Virtualisation
– Data access and management without having to know all of
the details.
– Original data is not moved, the user has virtual views of the
data stored in
existing databases
https://blogs.dxc.technology/2017/07/24/data-lakes-hubs-and-
warehouses-when-to-use-what/
https://blogs.dxc.technology/2017/07/24/data-lakes-hubs-and-
warehouses-when-to-use-what/
Storage of Data (p2)
• Data warehouse (traditional approach)
– A repository of data from various sources, partially re-
organised,

18. structured and used to support decision makers in the
organisation
– Takes data from data lake and transforms it (also a type of
DB)
• Database (DB)
– Relational DB: Organised collection of structured data
– Other DBs: Organised collection of semi-, quasi or
unstructured data
– For example, Graph database, in which the data is structured a
certain
way to determine relationships
https://blogs.dxc.technology/2017/07/24/data-lakes-hubs-and-
warehouses-when-to-use-what/
https://blogs.dxc.technology/2017/07/24/data-lakes-hubs-and-
warehouses-when-to-use-what/
Comparison Table

19. Task Data Hub (e.g.
that of MarkLogic)
Data Lake Data Virtualisation
Data ingestion Load raw data
Data migrated to
a DB and stays
there
Load raw data
Data migrated to a
DB then stored in a
HDFS*
See a virtual view of

20. the data
Data Model Multi-model Hadoop multiple file
model
Underlying system
model (see notes)
Search and
Query
Built in Varies depending on
tools
Queries optimised
and passed to the
underlying systems
Security Granular and

21. advanced
Can be poor Security controls
required for virtual
and underlying DB
* HDFS = Hadoop Distributed File System
https://www.marklogic.com/product/comparisons/data-hub-vs-
data-lake/
Comparison Table
Task Data Hub (e.g.
that of
MarkLogic)
Data Lake Data Virtualisation

22. Performance High
performance
Transactions and
analytics
High performance
analytics
High performance
Analytics, however
depends on underlying
infrastructure
Scalability Pentabyte
scalability *

23. Pentabyte
scalability
Only performs as well
as the slowest
underlying system
(and is impacted by
any issues in the
originating DBs)
https://www.marklogic.com/product/comparisons/data-hub-vs-
data-lake/
Activity 1: Quick Quiz
1. An unorganised repository of data is most likely to be

24. a. A database
b. A library
c. A data lake
d. Data virtualisation
2. No security is required for data virtualisation
a. True
b. False
3. Scalability is similar for a Data Hub and Data Lake?
a. True
b. False
Big Data Frameworks
• Hadoop is a distributed database (filing) system for big data

25. o Uses the MapReduce algorithm (see notes)
• Spark is an open-source processing engine
o Also described as a distributed general-purpose cluster-
computing
framework.
This Photo by Unknown Author is licensed under CC BY-ND
Factors Spark Hadoop MapReduce
Speed 100x faster than MapReduce Faster than previous
systems
Code name Scala Java
Data processing Batch, real-time, iterative,
interactive and graph
Batch processing

26. Ease of use Compact and easier than Hadoop complex
Caching Caches* the data in memory No caching
https://data-flair.training/blogs/spark-vs-hadoop-mapreduce/
https://blog.toright.com/posts/4369/apache-spark-
%E6%95%99%E5%AD%B8-%E7%94%A8-machine-learning-
%E8%BE%A8%E8%AD%98%E9%B3%B6%E5%B0%BE%E8%
8A%B1.html
https://creativecommons.org/licenses/by-nd/3.0/
Activity 2: Big Data Frameworks
• Apache Sparke is taking over from Hadoop or included in
Hadoop
installations
• Watch the video below
• https://www.youtube.com/watch?v=aUCLLJFSJ-g
Q. Using your slides and the information in the video, list the

27. various ways
in which the frameworks differ?
This Photo by Unknown Author is licensed under CC BY-ND
https://www.youtube.com/watch?v=aUCLLJFSJ-g
https://blog.toright.com/posts/4369/apache-spark-
%E6%95%99%E5%AD%B8-%E7%94%A8-machine-learning-
%E8%BE%A8%E8%AD%98%E9%B3%B6%E5%B0%BE%E8%
8A%B1.html
https://creativecommons.org/licenses/by-nd/3.0/
Traditional Data Warehouse Model
LO2
https://panoply.io/data-warehouse-guide/data-warehouse-
architecture-traditional-vs-cloud/
https://panoply.io/data-warehouse-guide/data-warehouse-
architecture-traditional-vs-cloud/
Newer Cloud-Based Warehouse

28. https://panoply.io/data-warehouse-guide/data-warehouse-
architecture-traditional-vs-cloud/
• For example, Panoply’s “Smart data infrastructure” with
Amazon Redshift and Amazon S3
https://panoply.io/data-warehouse-guide/data-warehouse-
architecture-traditional-vs-cloud/
Case Study 1: Storage via AWS
• Amazon Simple Storage Service (Amazon S3)
is a cloud storage service.
• Allows you to store and retrieve any amount of
data at any time, from anywhere on the web.
• Uses a simple and intuitive web interface of the
Amazon Web Services (AWS) Management
Console.
• Example AWS warehouse: the Amazon Redshift data

29. Warehouse (see notes)
https://aws.amazon.com/#
Activity 3: 10-min Research
• Check out the “Products” or “