The document discusses different types of data and analytics. It defines data as facts and figures that can be used to draw conclusions. Both quantitative and qualitative data are described. Quantitative data includes numbers that can be objectively measured, while qualitative data includes descriptions that may be subjectively measured. The document also discusses descriptive analytics, which interprets historical data to understand problems; predictive analytics, which uses data to predict future outcomes; and prescriptive analytics, which recommends optimal actions by combining constraints with other analytics.
Dear All, This is very comprehensive training on application of 7QC tools in industry. There is now a common demand in every industry to improve and control the process by achieving product quality with integrity. These 7-QC tools are very useful to fulfil industry demand by controlling the process. I am expecting your kind suggestions and comments to improve my presentation further. Thanks a lot everyone for your time to read this presentation. I hope it will definitely give some value addition in your routine life. Thanking you!
Dear All, I have prepared this presentation to get a better understanding of Statistical Process Control (SPC). This is a very informative presentation and giving information about the History of SPC, the basics of SPC, the PDCA approach, the Benefits of SPC, application of 7-QC tools for problem-solving. You can follow this technique in your day to day business working to solve the problems. Thanking you.
Overview of Lean Manufacturing and Six Sigma tools, comaprison between Lean Speed and Six Sigma Quality combining Lean with Six Sigma
Overview of DMAIC and SIX SIGMA FORMULA
On May 15, 2015, the USDA Food Safety Inspection Service (FSIS) released the final requirements for Hazard Analysis & Critical Control Points (HACCP) Systems Validations. Learn how to be ready, and avoid non-compliance and enforcement actions?
Saksham Sarode - Building Effective test Data Management in Distributed Envir...TEST Huddle
EuroSTAR Software Testing Conference 2010 presentation on Building Effective test Data Management in Distributed Environment by Saksham Sarode. See more at: http://conference.eurostarsoftwaretesting.com/past-presentations/
Big Data Analytics for Healthcare Decision Support- Operational and ClinicalAdrish Sannyasi
Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
Epoch provides training to students, professionals and corporate on SAS®, Data Management Activities and soft skills. Training includes Software Programming, Clinical, Analysis and Analytics modules, which can be availed by professionals with IT, Life Sciences, Medical, Statistics, MBA and such other backgrounds. Epoch is the pioneer in the courses designed of SAS designed for Clinical Programming world.
www.epoch.co.in, info@epoch.co.in
#bigdata
#hadoop
#sastraining
#epochsastraining
#sasonlinetraining
#clinicalprogramming
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#epochresearchinstitute
Introduction to Process Mining and its applicability to enterprise technology customer support. Please visit my blog at http://www.haimtoeg.com/?p=1881 for further discussion.
Dear All, This is very comprehensive training on application of 7QC tools in industry. There is now a common demand in every industry to improve and control the process by achieving product quality with integrity. These 7-QC tools are very useful to fulfil industry demand by controlling the process. I am expecting your kind suggestions and comments to improve my presentation further. Thanks a lot everyone for your time to read this presentation. I hope it will definitely give some value addition in your routine life. Thanking you!
Dear All, I have prepared this presentation to get a better understanding of Statistical Process Control (SPC). This is a very informative presentation and giving information about the History of SPC, the basics of SPC, the PDCA approach, the Benefits of SPC, application of 7-QC tools for problem-solving. You can follow this technique in your day to day business working to solve the problems. Thanking you.
Overview of Lean Manufacturing and Six Sigma tools, comaprison between Lean Speed and Six Sigma Quality combining Lean with Six Sigma
Overview of DMAIC and SIX SIGMA FORMULA
On May 15, 2015, the USDA Food Safety Inspection Service (FSIS) released the final requirements for Hazard Analysis & Critical Control Points (HACCP) Systems Validations. Learn how to be ready, and avoid non-compliance and enforcement actions?
Saksham Sarode - Building Effective test Data Management in Distributed Envir...TEST Huddle
EuroSTAR Software Testing Conference 2010 presentation on Building Effective test Data Management in Distributed Environment by Saksham Sarode. See more at: http://conference.eurostarsoftwaretesting.com/past-presentations/
Big Data Analytics for Healthcare Decision Support- Operational and ClinicalAdrish Sannyasi
Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
Epoch provides training to students, professionals and corporate on SAS®, Data Management Activities and soft skills. Training includes Software Programming, Clinical, Analysis and Analytics modules, which can be availed by professionals with IT, Life Sciences, Medical, Statistics, MBA and such other backgrounds. Epoch is the pioneer in the courses designed of SAS designed for Clinical Programming world.
www.epoch.co.in, info@epoch.co.in
#bigdata
#hadoop
#sastraining
#epochsastraining
#sasonlinetraining
#clinicalprogramming
#epochsasonlinetraining
#epochresearchinstitute
Introduction to Process Mining and its applicability to enterprise technology customer support. Please visit my blog at http://www.haimtoeg.com/?p=1881 for further discussion.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
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This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
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Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
13. CommonProblem-
SolvingMethodologies
PDSA (PDCA) DMAIC (Six Sigma) A3 (Toyota) 8D (Eight Disciplines)
Plan
Define Clarify the problem
Form team and collect data
Measure
Break down the problem Describe the problem
Set the target/goal Contain the problem (interim)
Analyze
Analyze root causes Analyze root causes
Develop countermeasures Identify corrective actions
Do Improve Implement countermeasures Implement corrective actions
Study (Check)
Control
Evaluate results Implement preventive actions
Act Standardize success Verify and congratulate team
18. Criteria Easier Problems Harder Problems
Time to solve Hours, days Months, years
Complexity Low, one-dimensional,
problem is well defined
High, multidimensional,
problem is ill defined
Scope Small, limited to one
process or one process
step
Large, problem spans
multiple processes or
organizational boundaries
Is there data? Relevant, high-quality data
are readily available
No relevant data, difficult to
measure, need to collect or
compile
Cause Single, identifiable Multiple, hard to identify,
interconnected
Success Measured, quantifiable Immeasurable, fuzzy
Solution Simple, straightforward Complex, multi-phased,
multi-dimensional
27. Problem Statement
Currently, the black anodizing process has very low
daily yields, usually below 40%, and is averaging
19% yield. This results in high scrap and rework
costs. Also, Components Inc.'s largest customer is
threatening to find another supplier if quality and on-
time delivery are not substantially improved. In the
past six months, scrap and rework costs have
totaled approximately $450,000 and on-time
delivery is below 60%.
revised
statement
32. The Cook,
Rice, Water, Salt,
Kitchen Temp,
Method Used,
Stove, Pot,
Cooking Temp
White Rice -
Tender, Fluffy,
Delicious
High-Level(Macro)ProcesMap
Make boiled white rice.
Inputs ProcesSteps
Outputs
33. To understand the process
1.Observe the process in action.
2.Interview people involved in the process.
3.Interview internal suppliers and internal
customers.
4.Review operating procedures or manuals.
36. What is Data?
• Data is the building block of modern economy
• Data can be in various formats
• Data can be subjective
• Data can be derived
• Data can be deceptive
37. Data
• Data: facts and figures from which conclusions can
be drawn
• Data set: the data that are collected for a particular
study
– Elements: may be people, objects, events, or otherentries
• Variable: any characteristic of an element
7
38. Data Types
• Quantitative data
– Numbers and things that can be measured
objectively
• Qualitative data
– Characters and descriptions that could have
subjective measurement
39. Quantitative Data
• Discrete
– Is a count e.g. number of students
– Whole numbers
• Continuous
– Is a linear measurement e.g. height, temperature
– Multiple levels of granularity
40. Qualitative Data
• Binary
– Two mutually exclusive categories
• Nominal
– Categories with no value or rank e.g. colors of candy
in a bag of M&M
• Ordinal
– Implicit or natural order e.g. High, Medium Low
42. Quantitative and Qualitative Variables
• Measurement: A way to assign a value of a
variable to the element
• Quantitative: the possible measurements of the
values of a variable are numbers that represent
quantities
• Qualitative: the possible measurements fall into
several categories
2
43. Cross-Sectional Data
• Cross-sectional data: Data collected at the
same or approximately the same point in time
• Time series data: data collected over
different time periods
3
44. Data Sources, Data Warehousing,
and Big Data
• Existing sources: data already gathered by public or private sources
–
–
–
–
Internet
Library
US Government
Data collection agency
• Experimental and observational studies: data we collect ourselves
for a specific purpose
–
–
Response variable: variable of interest
Factors: other variables related to response variable
4
45. Transactional Data, Data Warehousing,
and Big Data
• Companies hope to use past behavior and other
information to predict customer responses
• Data warehousing: a process of centralized data
management and retrieval
– Its objective is the creation and maintenance of a central repository for all
of an organization’s data
• Big data: massive amounts of data
–
–
Often collected in real time in different forms
Sometimes needing quick analysis
47. Business Analytics
• The use of traditional and newly developed
statistical methods, advances in IS, and
techniques from management science to
explore and investigate past performance
4
7
49. Descriptive Analytics
• Descriptive analytics is the interpretation of
historical data to better understand a problem
– Useful in discovering historical trends
– Identifying problems with data
– Providing preliminary relationship amongst
variables
51. Predictive Analytics Techniques
• Supervised learning
–
–
–
–
Linear regression
Logistic regression
Neural networks
Decision trees (classification trees and regression trees)
• Unsupervised learning
–
–
–
Cluster analysis
Factor analysis
Association rules
5
1
52. Prescriptive Analytics
5
2
Techniques that combine external and internal
constraints with results from descriptive or predictive
analytics to recommend an optimal course of action