Data Analytics and Data Warehouses

Abstract

This chapter focuses on how to extract information from package software systems. This information will be used for decision support system (DSS) purposes and typically be presented to the user in an on-line display format or as a report. The concept behind DSS is that it deals with data “after the fact,” meaning that the data are no longer in a production mode, but rather in a storage mode where it can be used for different forms of analytical processing. The major benefit of operating on processed data is that it cannot be changed and therefore can be accessed without concern for data integrity. Another salient issue is that because the data are not subject to change it can be copied multiple times, allowing for some interesting performance improvements and “flattening” of the data stored in the relational database. The referential integrity that was attained in a production database does not maximize performance for the query of data for reporting purposes. Almost all systems today need to determine how best to extract information for what is now being called “data analytics,” that is, the ability to understand and analyze the information contained in application software systems. Increasingly, CIOs are being held responsible for providing this information.