Introduction to Analytical Programming

1. BAS 150
Lesson 1:
Introduction to Analytical Programming

2. • Explain Analytical Programming
• Connect to SAS Studio
• Create a Logical Data Flow
Learning Objectives

3. Part 1:
Analytical Programming

4.  Programming (coding) to collect, explore and present large
amounts of data to discover underlying patterns, trends and
insights using statistical software.
 Statistics are applied every day – in research, industry and
government – to become more scientific about decisions that
need to be made.
 Data-driven decisions vs “Gut Driven” decisions
What is Analytical Programming?

5.  This course introduces statistical software for analytics
 Topics include utilization of analytical and statistical software
packages for data management, data visualization, and
exploratory data analysis.
 Upon completion, students should be able to use statistical
programming tools to conduct descriptive analytics.
 Essential for making data-based decisions in EVERY field.
Analytical Programming (1 of 3)

6. The course has five distinct parts:
1) Getting started with analytical programming
o Logic
o Technology
2) Foundational programming skills
o Nuts and bolts of programming
o Fostering good programming habits
o Getting external data sets into SAS
o Constructing an analysis data set
Analytical Programming (2 of 3)

7. 3) Reporting on your analysis
o Producing customized tables
o Generating more attractive output
o Producing high-quality graphical displays.
4) Creating descriptive statistics and summaries
5) Advanced topics, tricks and tips
Analytical Programming (3 of 3)

8. Software Review (1 of 4)

9. Software Review (2 of 4)

10. Software Review (3 of 4)

11. Software Review (4 of 4)

12.  Still the most frequently used business analytics tool today.
 91 of the top 100 companies on the 2015 Fortune Global
500® are SAS customers.
 SAS says that the #1 most valuable career skill is the
understanding of their data analysis software. This skill
commands the highest salary premium at SAS (+6.1%).
o “Money and PayScale analyzed 54 million employee profiles across
350 industries, with 15,000 job titles—from entry-lefvel workers to top
execs. The stuydy compared people with the same title, age, location
and experience, isolating the specific skills (from a universe of about
2,300) correlated with higher pay, advancement, and career
opportunity.” (Source)
Why SAS?

13.  Began as a statistical package
 Also allows users to:
o Store data
o Manipulate data
o Create reports
 PDF
 Excel
 HTML
 XML
 RTF / Word
 Etc. Etc. Etc.
What is SAS? (1 of 2)

14.  Also allows users to:
o Create graphs
o Create maps
o Send e-mails
o Create web applications
o Create iPhone Apps
o Access R
o Schedule regularly run reports
What is SAS? (2 of 2)

15. • SAS University Edition
• http://www.sas.com/en_us/software/university-edition.html
SAS University Edition provides free access to SAS software quickly and easily
for anyone to learn quantitative analysis. SAS University Edition makes writing
and submitting code easy, with a powerful graphical interface to SAS advanced
statistical analysis software.
In addition, free e-learning resources and online tutorials are available to help
users get started or to get help with specific tasks in SAS.
Software

16. Part 2:
Coding Mindset

17.  What does it take to become a good SAS programmer?
o Thinks logically
o Organized
o Attention to detail
o Looks for ways to be more efficient
o Can interpret and explain results clearly
o Focused on results
Coding Mindset (1 of 2)

18. Coding Mindset (2 of 2)
Critical tool in your analytical toolbox…
 “Logical Data Flow Map”
o The end-to-end flow of data
o Raw data Actionable insights
o Begin with the end in mind?

19. $$$
Actionable
InsightsClean
Normalize
Subset
Analyze
Inventory of Products
Cost of Products Sold
Customer Purchases
3
Show
2
Code
1
Data
Logical Data Flow Map Example

20.  Begin with where the data can be found
o Questions to ask…
 “Where is the data stored?”
 “What type of data is this?”
 “What format is the data saved?”
1
Data
Logical Data Flow Map

21. Inventory of Products - “ IT Data Warehouse” - XML file format
Cost of Products Sold – “Accounting department” – Excel file format
Customer Purchases - “Point of Sale data” – CSV file format
1
Data
Logical Data Flow Map
Example: Sources of Data

22.  Data management & analysis
o Questions to ask…
 “Do I need to clean the data?”
 “How do I merge the data?”
 “What types of analytics do I need to uncover insights?”
 “How do I subset the data to report the insights?”
2
Code
Logical Data Flow Map

23. 2
Code
Logical Data Flow Map
Example

24.  End with an actionable insight to share
o Questions to ask…
 “Who is my audience?”
 “What type of reports do they want to see?”
 “How do I format output to easily “see” the insights?”
 “Is the insight actionable?”
3
Show
Logical Data Flow Map

25. $$$
3
Show
Logical Data Flow Map
Example

26. $$$
Actionable
InsightsClean
Normalize
Subset
Analyze
Inventory of Products
Cost of Products Sold
Customer Purchases
3
Show
2
Code
1
Data
Logical Data Flow Map
Example

27. Learning objectives…
 “Explain Analytical Programming” - Lecture; Video
 “Connect to SAS Studio” - Video; Homework
 “Create a Logical Data Flow Map” - Homework
Summary

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Except where otherwise stated, this work by Wake Technical Community College Building Capacity in
Business Analytics, a Department of Labor, TAACCCT funded project, is licensed under the Creative
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