The Data Warehouse Deluxe
You’ll most likely focus most of your data warehousing-related activities on the data warehouse deluxe environment, as shown in this figure. Data from many different sources converge in these real data warehouses, which make available a wealth of architectural options that you can tailor to meet your specific needs.
Subject areas and data content of a data warehouse deluxe
A data warehouse deluxe contains a broad range of related subject areas — everything (or most things) that would follow a natural way of thinking about and analyzing information.
Suppose that in your job at a wireless division of a telephone company, you analyze the sales of services such as in-network minutes, out-of-network minutes, text messaging, Internet access, and other mobile usage to consumer households.
In a data warehouse deluxe, you will likely find not only the subject area of consumer wireless services (among other items), but also these elements:
Consumer basic calling revenues and volumes
Consumer long-distance calling revenues and volumes
Consumer wireless calling revenues and volumes
Business wireless services
Business basic calling revenues and volumes
Business long-distance calling revenues and volumes
Business wireless calling revenues and volumes
Internet access (DSL) services
Internet revenues and volumes
The subject range is broader than a data warehouse lite for a data warehouse deluxe because
The user base is broader (more organizations have their people use the data warehouse).
The scope of any given user’s queries and reports is broader than just one or two subject areas. For example, a user might run reports comparing trends in add-on services for businesses and consumers to see where to concentrate future sales-and-marketing efforts.
When you implement a data warehouse deluxe, you almost always need access capabilities (unlike with a data warehouse lite), in addition to simple results reporting. Therefore, although you might be able to use standard reports as a starting point when you’re deciding what should be in your warehouse, that’s rarely enough. Follow these steps to thoroughly understand your source systems:
Take a complete inventory of available information.
This inventory is called a source systems analysis.
Review each candidate source element and answer these questions:
What data do you need to include in the data warehouse and what should you leave out?
What information should be summarized and what should be left at the detailed level?
What data should remain in the data warehouse forever, and what data should you purge from the data warehouse after it has aged?
What else do you need to know about the data before you put it in your data warehouse?
This step is one of the most severe tests of how well the IT people and business users get along throughout the data warehousing project.