How to Design and Document a Dimensional Model 443 in Software

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18 How to Design and Document a Dimensional Model 443
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A conformance framework is the centerpiece of a dimensional design. This holds true whether you are designing a dimensional data warehouse in the style advocated by Ralph Kimball, departmental data marts in the style advocated by W.H. Inmon, or stand-alone data marts. As recommended later in this chapter, it is essential to document how dimensions conform, and create a matrix that links fact tables to the key dimension tables in the design. The details of slow change processing will be addressed in depth later, when you produce a detailed design. At this point, however, it is useful to consider some key requirements that are likely to affect the capabilities of the solution and the complexity of the ETL process. It is safest to proceed from the assumption that most changes will be type 2, but where is that not the case Are there changes that are not significant Are there cases that call for a type 3 change, or a hybrid change These will have a significant impact on the ETL process; write them down. Last, remember that, in many cases, a single process will require more than one fact table. The most common examples are transaction and snapshot pairs, or transaction and accumulating snapshot pairs, as described in 11. If you find you have modeled any of these designs, ask yourself if a complementary fact table would be useful. Review your interview notes to find out. Other forms of derived tables, as described in 14, may be useful for specific kinds of reporting.
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Part VI
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If You Get Stuck Sometimes, efforts to follow the first four steps stall from the start: identifying the process. As noted in 4, processes can usually be decomposed into subprocesses, so it is hard to know where to begin. The preceding example took one process, Sales, and broke it down into six processes, for proposals, orders, returns, and so forth. This breakdown may not be evident. If the four steps are not working for you, you may want to try another approach. Review your interview notes, making a list of candidate dimension tables. Don t worry about getting these exactly right; you will be able to revise them later. Next, make a list of candidate facts (individual facts, not fact tables), and cross-reference them with the candidate dimension tables. This can be done in a matrix, as in Figure 18-2. The rows of the matrix represent facts that have been identified from interview notes. The columns represent candidate dimensions. The checkmarks indicate the level of dimensional detail at which each fact is available. Once you have made a cross-reference of facts and dimension tables, look for facts that share identical dimensionality. You can re-sort your matrix so that they appear together. In Figure 18-2, these groupings are shaded in gray and white bands. The facts in each group may belong together in a single fact table. Ask yourself if they share the same level of dimensional detail and if they are available at the same time. As you learned in 4, the answer to these two questions will help you determine if they belong together in a single fact table. Once you have identified these natural affinities, you have a group of candidate processes. They can be used as the basis for individual fact table designs. Each one can now be taken through the four steps described earlier.
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PART VI
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Number of sales calls Quantity proposed Proposal dollars Quantity ordered Order dollars Cost dollars Margin dollars Revenue dollars Quantity shipped Quantity returned Return dollars
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Figure 18-2 Affinities among facts provide process clues
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Conducting a Design Review
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As the high-level dimensional design is being worked out, it should be documented, as described later in this chapter. Once this is complete, it is essential to conduct a design review. This review allows a variety of other interested parties to contribute in a positive manner.
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Impacts of Design Decisions The principles of dimensional design do not dictate a single correct design solution for a given process. Even if you follow all the best practices laid out in this book, it will be necessary to make some choices. You have seen several examples of decisions made during the design process:
How to break up related things into dimension tables ( 6) Whether use of an outrigger is justified ( 7) When the extra effort of a hybrid slow change is necessary ( 8) Choosing to develop a bridge table versus keeping things safe for end users (s 9 and 10) Deciding if an accumulating snapshot is warranted versus computing correlations in queries ( 11) Opting to design core and custom stars as opposed to placing all attributes in a single star ( 13) Determining if derived tables are justified for simplifying certain reports ( 14)
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