Dealing with storage and memory issues

This section will cover issues with storage and memory when using SAS for big data. It will cover the following:

• How SAS dealt with competition from structured query language (SQL) for data storage

• How PROC SQL works and can be used in data warehouse processing

• Considerations about memory and storage that need to be made when using SAS in a data warehouse in modern times

• How SAS can work in the cloud

Avoiding memory issues

Even as SAS got more powerful, datasets kept getting bigger, and there were always challenges with running out of memory during processing. For example, using WHERE instead of IF when reading in data would not only reduce CPU usage and the time it took for code to run, it would also prevent unnecessary usage of memory. Even today, tuning SAS code may be necessary to avoid memory issues.

In a data warehouse, mart, or lake, datasets that were transformed in SAS may be stored outside of SAS in SAS...