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.
Table of Contents (18 chapters)
1
Section 1: Managing Data in a SAS Data Warehouse
7
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
12
Section 3: Using SAS When Serving Warehouse Data to Users

Summary

This chapter gave an overview of alternatives to debugging and troubleshooting SAS code, specifically data step code. First, we discussed the importance of well-formed and well-formatted code, especially with respect to ETL protocols in a data warehouse that might live on for a long time. We demonstrated how to leverage messages in the log for guidance when troubleshooting data steps, and how to use the PUT statement to write values to the log during a data step. Next, we looked specifically at ways to troubleshoot do loop code and went over debugging functions that SAS has built into Enterprise Guide. Finally, we covered approaches to debugging and troubleshooting macros.

Because the SAS code is so complicated, building data step code that processes big data usually turns into a big project with a lot of code. With more code, there are more opportunities to need to edit the code, especially to accommodate improvements in the data warehouse. This chapter gave a practical...