150 High-Function Business Intelligence in e-business
4.1 Introduction
We describe typical business queries in the following industries:
? Retail
? Finance
? Sports
This is the format we followed for each industry sector:
1. A statement of the business requirement
2. Data fields/attributes required to address the requirement
3. DB2 UDB functions used in the queries
4. The steps involved in addressing the requirement, and for each step:
– The SQL required
– The result set
– How the result set is converted for visualization
– Visualization of the result
The data for our queries come from different sources, and some of these are
documented in Appendix B, “Tables used in the examples” on page 235, while
the content of others are listed in the business requirement solution.
4.1.1 Using sample data
In many cases, the volume of data available may be very large, and it may not be
cost-effective or timely enough to analyze the entire data. In such cases, it would
be appropriate to take a representative sample of the data and perform analyses
on it instead. An efficient and cost-effective sampling function can have a
significant impact on the scalability of a system involving large volumes of data
that typify the e-business environment.
Attention: Many of these business queries problems apply to other industries
as well
Important: Source data to answer the business query varies from
organization to organization. We therefore assume that appropriate extraction,
cleansing, and transformation of the data has been done to present it in one or
more normalized tables for our queries. The latency of the data and the
end-to-end performance perception of the business query is impacted by the
efficiency of the extraction and transformation process.
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