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Introduction to Analytics
Alex Meadows
October 21, 2015
24.10.15 Introduction to Analytics 2
Contents
● What is Analytics?
● Why Care?
● The Analytics Landscape
● Components of Analytics
24.10.15 Introduction to Analytics 3
What is Analytics?
● The science (and art!) of applying statistical techniques to data sets to obtain
actionable information
● Part of Business Intelligence
● Multidimensional discipline
– Data Analysis
● Data Modeling
● Data Quality
● Data Transformation
– Data Visualization
– Math/Statistics
– Machine Learning
● Within the past five years it has become more accessible and easier to use
in practice
● Usually a latter-stage evolution of business decision making
24.10.15 Introduction to Analytics 4
What Is Analytics?
● Obtain “good” data
● Analyze
● Turn into a human readable story
Image Source: http://www.dataincolour.com/about
24.10.15 Introduction to Analytics 5
Why Care?
● Health Care
– Predict how long a patient will stay as soon as they are admitted
– Predict what a patient has based on symptoms and past medical history
● Manufacturing
– Predict when a machine will need maintenance before it breaks down
– Determine better production processes to reduce waste
● Education
– Determine what educational techniques provide desired results
– Predict students who need tutoring based on the first few weeks of
attendance
24.10.15 Introduction to Analytics 6
24.10.15 Introduction to Analytics 7
Overlapping Skills
Source: Back In Business, Klimberg, Miori (www.informs.org)
24.10.15 Introduction to Analytics 8
Analytics Components – Data Modeling
● Providing structure to data based on metadata
● Relational Database Normalization – (reduction of duplication)
– Single source
● Data Warehousing
– Integration of many sources
– Provides cleansed data for reporting/dashboards, analysis, and analytics
● Ontological – metadata in plain language
– Triple stores (subject, predicate, object)
– Integration of one or many sources
24.10.15 Introduction to Analytics 9
Analytics Components – Data Quality
● Measuring data to determine if it is fit for purpose
● Spot the issues:
First Name Last Name Birth Date
1Tom Smith 01/01/89
2Barbara Jone 04/12/43
3Thomas Smith 01/01/1989
4Jessica Martin 03/19/2084
24.10.15 Introduction to Analytics 10
Analytics Components – Data Transformation
● Transforming the data to match business requirements and correct data
quality issues
First Name Last Name Birth Date
1Tom Smith 01/01/89
2Barbara Jone 04/12/43
3Thomas Smith 01/01/1989
4Jessica Martin 03/19/2084
Before
First Name Last Name BirthDate
2Barbara Jones 04/12/1943
3Thomas Smith 01/01/1989
4Jessica Martin 03/19/2084
After
24.10.15 Introduction to Analytics 11
Analytics Components – Data Visualization
● Graphical representation of data
● Useful to tell the story the data provides
24.10.15 Introduction to Analytics 12
Analytics Components – Data Visualization
24.10.15 Introduction to Analytics 13
Analytics Components – Statistics
● Deeper analysis of data to determine hidden trends and make predictions
● Feeds other components of Business Intelligence to make smarter decisions
Scatterplot Source: https://teamsite.smu.edu.sg/wiki/stats/Wiki/Linear%20Regression%20in%20STATA.aspx
24.10.15 Introduction to Analytics 14
Analytics Components – Machine Learning
● Train computers to learn trends and understand data
● Provide action to the analytics
24.10.15 Introduction to Analytics 15
Analytic Ladder
Source: Competing on Analytics, 2007, Davenport and Harris

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Introduction To Analytics

  • 1. Introduction to Analytics Alex Meadows October 21, 2015
  • 2. 24.10.15 Introduction to Analytics 2 Contents ● What is Analytics? ● Why Care? ● The Analytics Landscape ● Components of Analytics
  • 3. 24.10.15 Introduction to Analytics 3 What is Analytics? ● The science (and art!) of applying statistical techniques to data sets to obtain actionable information ● Part of Business Intelligence ● Multidimensional discipline – Data Analysis ● Data Modeling ● Data Quality ● Data Transformation – Data Visualization – Math/Statistics – Machine Learning ● Within the past five years it has become more accessible and easier to use in practice ● Usually a latter-stage evolution of business decision making
  • 4. 24.10.15 Introduction to Analytics 4 What Is Analytics? ● Obtain “good” data ● Analyze ● Turn into a human readable story Image Source: http://www.dataincolour.com/about
  • 5. 24.10.15 Introduction to Analytics 5 Why Care? ● Health Care – Predict how long a patient will stay as soon as they are admitted – Predict what a patient has based on symptoms and past medical history ● Manufacturing – Predict when a machine will need maintenance before it breaks down – Determine better production processes to reduce waste ● Education – Determine what educational techniques provide desired results – Predict students who need tutoring based on the first few weeks of attendance
  • 7. 24.10.15 Introduction to Analytics 7 Overlapping Skills Source: Back In Business, Klimberg, Miori (www.informs.org)
  • 8. 24.10.15 Introduction to Analytics 8 Analytics Components – Data Modeling ● Providing structure to data based on metadata ● Relational Database Normalization – (reduction of duplication) – Single source ● Data Warehousing – Integration of many sources – Provides cleansed data for reporting/dashboards, analysis, and analytics ● Ontological – metadata in plain language – Triple stores (subject, predicate, object) – Integration of one or many sources
  • 9. 24.10.15 Introduction to Analytics 9 Analytics Components – Data Quality ● Measuring data to determine if it is fit for purpose ● Spot the issues: First Name Last Name Birth Date 1Tom Smith 01/01/89 2Barbara Jone 04/12/43 3Thomas Smith 01/01/1989 4Jessica Martin 03/19/2084
  • 10. 24.10.15 Introduction to Analytics 10 Analytics Components – Data Transformation ● Transforming the data to match business requirements and correct data quality issues First Name Last Name Birth Date 1Tom Smith 01/01/89 2Barbara Jone 04/12/43 3Thomas Smith 01/01/1989 4Jessica Martin 03/19/2084 Before First Name Last Name BirthDate 2Barbara Jones 04/12/1943 3Thomas Smith 01/01/1989 4Jessica Martin 03/19/2084 After
  • 11. 24.10.15 Introduction to Analytics 11 Analytics Components – Data Visualization ● Graphical representation of data ● Useful to tell the story the data provides
  • 12. 24.10.15 Introduction to Analytics 12 Analytics Components – Data Visualization
  • 13. 24.10.15 Introduction to Analytics 13 Analytics Components – Statistics ● Deeper analysis of data to determine hidden trends and make predictions ● Feeds other components of Business Intelligence to make smarter decisions Scatterplot Source: https://teamsite.smu.edu.sg/wiki/stats/Wiki/Linear%20Regression%20in%20STATA.aspx
  • 14. 24.10.15 Introduction to Analytics 14 Analytics Components – Machine Learning ● Train computers to learn trends and understand data ● Provide action to the analytics
  • 15. 24.10.15 Introduction to Analytics 15 Analytic Ladder Source: Competing on Analytics, 2007, Davenport and Harris