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Dimensional data models (a.k.a. star schemas) are a crucial component of the presentation layer of data warehouses and data marts, because that is the format in which business-intelligence analysts expect to find their data. Yet, so many decision-support environments based on Oracle attempt to live with star schemas without using star transformations. The reasons vary from lack of understanding to practical impediments related to ETL processing. This presentation will explain the justification for the star transformation mechanism, including comparisons to other execution plans, how to implement, how to optimize, and how to troubleshoot.
Three Things Attendees will learn:
1. Why dimensional data models are crucial in data warehousing
2. Using star-joins and star-transformation joins in a dimensional data model
3. How to improve on star-transformation joins using bitmap-join indexes
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