Book Image

Mastering SAS Programming for Data Warehousing

By : Monika Wahi
Book Image

Mastering SAS Programming for Data Warehousing

By: Monika Wahi

Overview of this book

SAS is used for various functions in the development and maintenance of data warehouses, thanks to its reputation of being able to handle ’big data’. This book will help you learn the pros and cons of storing data in SAS. As you progress, you’ll understand how to document and design extract-transform-load (ETL) protocols for SAS processes. Later, you’ll focus on how the use of SAS arrays and macros can help standardize ETL. The book will also help you examine approaches for serving up data using SAS and explore how connecting SAS to other systems can enhance the data warehouse user’s experience. By the end of this data management book, you will have a fundamental understanding of the roles SAS can play in a warehouse environment, and be able to choose wisely when designing your data warehousing processes involving SAS.

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Table of Contents (18 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
1
Section 1: Managing Data in a SAS Data Warehouse
Section 1: Managing Data in a SAS Data Warehouse
Free Chapter
2
Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse
Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse
Technical requirements
Using original versions of SAS
Accessing data in SAS
Improving I/O
Dealing with storage and memory issues
Using SAS in modern warehousing
Summary
Questions
Further reading
3
Chapter 2: Reading Big Data into SAS
Chapter 2: Reading Big Data into SAS
Technical requirements
Reading data extracts into SAS
Using the SAS XPT format
Working with other file formats
Dealing with difficult data
Summary
Questions
Further reading
4
Chapter 3: Helpful PROCs for Managing Data
Chapter 3: Helpful PROCs for Managing Data
Technical requirements
PROCs for understanding data
Using labels and formats in processing
Viewing data in SAS
Summary
Questions
Further reading
5
Chapter 4: Managing ETL in SAS
Chapter 4: Managing ETL in SAS
Technical requirements
Setting up an analytic environment
Planning for data transformation
Developing policy
Summary
Questions
Further reading
6
Chapter 5: Managing Data Reporting in SAS
Chapter 5: Managing Data Reporting in SAS
Technical requirements
Using the ODS for data files
Using the ODS for graphics files
SAS PROCs designed for reporting
Summary
Questions
Further reading
7
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
8
Chapter 6: Standardizing Coding Using SAS Arrays
Chapter 6: Standardizing Coding Using SAS Arrays
Technical requirements
Understanding examples of arrays used to create variables
Conditions and index variables in array processing
Limitations of arrays
Summary
Questions
Further reading
9
Chapter 7: Designing and Developing ETL Code in SAS
Chapter 7: Designing and Developing ETL Code in SAS
Technical requirements
Planning the ETL approach
Creating transformation code
Summary
Questions
Further reading
10
Chapter 8: Using Macros to Automate ETL in SAS
Chapter 8: Using Macros to Automate ETL in SAS
Technical requirements
Creating macros out of data step code
Storing and calling macros
Loading transformed data
Summary
Questions
Further reading
11
Chapter 9: Debugging and Troubleshooting in SAS
Chapter 9: Debugging and Troubleshooting in SAS
Technical requirements
Debugging data step code
Debugging the do loop code
Debugging SAS macros
Summary
Questions
Further reading
12
Section 3: Using SAS When Serving Warehouse Data to Users
Section 3: Using SAS When Serving Warehouse Data to Users
13
Chapter 10: Considering the User Needs of SAS Data Warehouses
Chapter 10: Considering the User Needs of SAS Data Warehouses
Technical requirements
Needs of data warehouse users
Data stewardship for serving warehouse users
Data stewardship for serving warehouse developers
Summary
Questions
Further reading
14
Chapter 11: Connecting the SAS Data Warehouse to Other Systems
Chapter 11: Connecting the SAS Data Warehouse to Other Systems
Technical requirements
Serving SAS to other systems
Connecting to non-SAS data storage
Innovations in integrating SAS in reporting functions
Summary
Questions
Further reading
15
Chapter 12: Using the ODS for Visualization in SAS
Chapter 12: Using the ODS for Visualization in SAS
Technical requirements
The basics of using the ODS for data visualization
Serving SAS data to the web with the ODS
Using SAS and R for visualizations
Considerations when reporting SAS warehouse data
Summary
Questions
Further reading
16
Assessments
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
17
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Questions

  1. How does an analyst tell what the variable names mean and what the coded levels for categorical variables mean in a dataset?

  2. PROC FREQ is for creating frequency tables about categorical variables, and PROC UNIVARIATE is for producing summary statistics about continuous variables. Therefore, why would a person preparing data for loading into a data warehouse ever use PROC FREQ on a continuous variable?

  3. Why is it helpful to plan transformed variables in a data dictionary before developing ETL code?

  4. How does suppressing values as missing in a continuous variable impact PROC UNIVARIATE output?

  5. Imagine you were working on a data warehouse with stock market data. In your data warehouse, you had the value of the stock market at the time of closing every day. What are some classification variables you could make that might improve how the users of the data warehouse were served?

  6. Imagine you had some weather data from a tropical region. After checking a data...

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