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This simplified SQL is much easier to write and understand, reducing the skill level required to perform process comparisons. This may be a nice to have feature, but there are other factors that may make the merged fact table a must have.

If you ask a systems or network administrator what is required to solve data protection problems in their own environments, you ll likely get answers that mention factors such as redundancy, fault-tolerance for hardware and software, and backup hardware and software. These are good answers, but they focus only on the technical side of things. Often, the real challenge of creating a data protection plan is coordinating this effort with all areas of your company. In 1, we covered the importance of defining why we are protecting information. A complete data protection plan takes into account both the management and people side and the technical issues involved with performing backups. In this section, we ll look at some best practices for performing data protection on the management side.

In addition to simplifying queries, a merged fact table can greatly improve performance. In the case of the goal versus actual comparison for the orders process, the benefit may be minimal. Drilling across two data sets can be completed with great efficiency, particularly when a small number of shared dimensions are in the result set, and those dimensions take on a relatively small number of distinct values. The performance advantage of a merged fact table is more pronounced when data sets are larger, or when comparing a large number of processes. In 4, for example, a sales report was described that pulled together data from four fact tables. Sales calls, proposals, orders, and revenue were combined into a single report, organized by quarter and region, as shown in Figure 4-13. In this case, performance may be significantly improved by a merged fact table.

The simplest data integrity constraint requires that a column contain a non-NULL value. The ANSI/ISO standard and most commercial SQL products support this constraint by allowing you to declare that a column is NOT NULL when the table containing the column is first created. The NOT NULL constraint is specified as part of the CREATE TABLE

Profitability analysis is another common example where a merged fact table can provide significant performance improvements. Studying profitability requires the comparison of revenue and costs, which are generated by separate processes represented by separate stars. A manufacturer of consumer products, for example, may have stars that capture sales, shipments, returns, commission payments, marketing promotions, manufacturing costs, and other overhead activities. Profitability analysis brings these disparate processes together over a set of common dimensions such as time or product. Bringing together more components can create a finer picture of profitability but also impacts performance. A merged fact table for profitability analysis removes this bottleneck.

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Many packaged query and reporting tools can be configured to recognize situations that require drilling across and then automate the process. Using some tools, it is also possible to assemble a drill-across report manually. Three methods of drilling across were illustrated in Figure 4-14. As noted in 4, some business intelligence tools cannot be used in any of these manners. Others present configuration challenges that prevent such use. When the data warehouse architecture does not include tools that can be used to drill across, the merged fact table becomes an essential part of the dimensional design. Merged fact tables must be designed and implemented to support all cross-process reporting. The drill-across activity is performed during the ETL process; the resulting merged fact tables support cross-process analysis without requiring the use of multiple stars. TIP A merged fact table consolidates facts from multiple fact tables by precomputing the drill-across activity. This makes cross-process analysis queries easier to write and can improve performance. If the available reporting tools do not support drilling across, a merged fact table will enable comparisons that would otherwise be impossible.