7
Dimension Table ETL
The next three chapters focus on the problems and solutions of data warehouse extraction, transformation, and loading (ETL) and business intelligence (BI) processing. This chapter examines how to process dimension tables using SSIS. Dimension tables are a data warehouse concept, which this chapter describes. The chapter then discusses how to move data from your data sources to your data warehouse dimension tables. Similar to this, Chapter 8 reviews the same things, but only applied for fact tables. Chapter 9 also covers BI, but looks at the integration of SSIS with SQL Server Analysis Services (SSAS). Integration between SSIS and SSAS involves cube and dimension processing, as well as SSAS data mining querying and training.
This chapter is divided into two Problem-Design-Solution sections. The first lays out the fundamental dimension ETL problem and then walks you through the basic design and solution with SSIS. The second problem deals with advanced dimension ETL that you may experience when dealing with high volumes or more complex dimension types.
Problem — Fundamental Dimension ETL
Arguably, when looking at the development time investment required for a data warehouse ETL solution, dimension table ETL takes the longest and is the most complex component. You may have experienced this time investment, especially when the requirements call for tracking the history of changes that a dimension goes through.
Does this user requirement sound familiar: “I want ...
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