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

Serving SAS to other systems

SAS is known for its ability to conduct ETL protocols on very large datasets. While other products have this capability, SAS also has the ability to conduct advanced statistical analyses, such as regressions. When compared to data warehouse storage software from other companies, such as Oracle's SQL, SAS is superior when it comes to the capacity to perform analytic functions. Even creating a contingency table such as the one produced by PROC FREQ can be overwhelming in terms of processing effort when attempted by other data warehouse software.

However, even though SAS has evolved over time, the continued difficulty in programming efficient I/O in SAS through the sophisticated use of data step language continues to hamper SAS when it competes with other products. This is why, traditionally, SAS data warehouses were only constructed to serve analysts who were planning on analyzing the data using SAS as the analytic software. That way, the only I/O...