In many organizations the amount of data we deal with increases far faster than the hardware and IT infrastructure to support them. As a result, we encounter significant bottlenecks and I/O bound processes. However, clever use of SAS^® software can help us find a way around. In this paper we will look at the clever use of PROC OLAP to show you how to address I/O bound processing spread I/O traffic to different servers to increase cube building efficiency. This paper assumes experience with SAS^® OLAP Cube Studio and/or PROC OLAP.

Today's business needs require 24/7 access to your data in order to perform complex queries to your analytical store. In addition, you might need to periodically update your analytical store to append new data, delete old data, or modify some existing data. Historically, the size of your analytical tables or the window in which the table must be updated can cause unacceptable downtime for queries. This paper describes how you can use new SAS^® Scalable Performance Data Server 5.1 cluster table features to simulate transaction isolation in order to modify large sections of your cluster table. These features are optimized for extremely fast operation and can be done without affecting any on-going queries. This provides both the continuous query access and periodic update requirements for your analytical store that your business model requires.