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Historically, most data warehouse initiatives have been sponsored
either by the marketing or the finance department, and focus
on the corresponding data and applications.
Traditional warehouse applications cover a wide range of
industries and functional disciplines, including:
- Finance - budgeting, performance monitoring (e.g. balanced
scorecard);
- Sales & marketing – sales analysis & forecasting,
direct mail, campaign management, market segmentation and
one to one marketing;
- Retail – sales performance analysis, basket analysis,
loyalty cards, promotions and inventory management;
- Financial services – fraud detection;
- Banking – credit scoring, product profitability (e.g.
activity based costing) and customer profitability.
More recent examples, some supporting more sophisticated
types of analysis, include:
- Travel & leisure - yield management;
- Pharmaceuticals - clinical trials;
- Insurance - underwriting analysis;
- Telecommunications - billing data mining;
- Marketing – trend analysis of channel switching behaviour
- Utilities – demand forecasting.
As the volume of data that can be effectively handled in
a warehouse environment increases with advances in hardware,
organisations are constructing ever more detailed databases
to help them understand customer behaviour. At the same time,
the Internet is making it easier to deliver information outside
of the organisation. These changes are creating opportunities
in the following areas:
There are numerous vendor-sponsored articles on the web describing
successful product implementations. In depth case histories
and independent project reviews are much harder to find (see
case studies).
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OVERVIEW
