Quick and dirty business intelligence, part two

Quick and dirty business intelligence, part two

The other approach to a quick and dirty custom business intelligence environment is to actually model the target with something resembling a dimensional schema, then map source data to the model. As opposed to the first approach, described yesterday, this approach will provide the users with a larger variety of usage possibilities. And, let's face it, most of the time, these quick and dirty business intelligence environments are built without much view of what the usage will be.

The modeling also facilitates integration and avoids a large transition effort from accessing an operational model to accessing a completely different schema. This approach will take longer than the first, but your odds of success will be higher with modeled data.

There are obvious limitations of modeling efforts that are quick and dirty, but data access tools can, without much IT effort, do much more for the user with a schema modeled for access. Time, at a premium in these quick projects, will be spent on the ETL mapping. Knowing the limitations of the two approaches and the ability levels of your team should help you determine which path to take.

Among the variety of shortcomings of leaving any quick and dirty approach up in production is the probability that such an approach lacks the sourcing of changed data only, probably only implements Type 1 slowly changing dimensions, lacks metadata and lacks varied access methods. Be sure to augment this initial

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system drop with more robustness along these lines.

For more information, check out searchCRM's Best Web Links on Business Intelligence and Data Analysis.


This was first published in January 2002

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