Business Intelligence: The Savvy Manager's Guide: Getting Onboard with Emerging IT
This quick reference guide overviews the best practices, tools, methods, and processes used to transform an organization's data into actionable knowledge.
TABLE OF CONTENTS Business Intelligence: The Savvy Manager's Guide: Getting Onboard with Emerging IT
Chapter 6: Data Warehouses, Online Analytical Processing, and Metadata
The hub of the business intelligence (BI) environment is the data warehouse, which is a centralized repository of data that has been compiled from a number of disparate data sources and is in turn used to power the analytical processing from which business value is derived. For the savvy manager to get the high-level view of the data warehouse, he or she must first be aware of the differences between traditional entity-relationship models and dimensional modeling, which is more suitable to the data warehouse environment.
The importance of data modeling in an analytical context, coupled with managing the metadata associated with that data, has evolved as a critical component to the BI environment. In this chapter we will look at data modeling, online analytical processing (OLAP), and metadata management, all of which incorporate ways to represent information for the purposes of BI.
The Business Case
There is a significant difference between the traditional use of databases for business purposes and the use of databases for analytical purposes. The traditional use revolves around transaction processing as the means by which a business's operation is modeled. The processes that surround the translation of a business operation into an operational system concentrate on two ideas: (1) Business requirements reflect interactions and relationships between modeled entities; (2) each discernable business activity can be described as a sequence of transactions grouped together as a single virtual operation to capture the effects of that activity in the model.
The evolution of relational database systems to accommodate...
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