barcode vb.net 2010 Part V in Software

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Part V
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PART V
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TIP A merged schema should be used only when comparing processes. Single-process analysis should be conducted using the original first-level dimensional structures. In some cases, it may be useful to include each territory, even if there are no sales, but notice that the merged fact table does not necessarily facilitate this. A zero is recorded for the Eastern territory because there is a goal. If there is another territory for which there is no goal, that territory will not appear on the report. The occurrence of zero-valued rows will appear to be random. An alternative technique should be used if an orders report should include all territories. This may be supported by features of the reporting tool or handled with SQL.
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Including a Nonshared Dimension
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When comparing facts from two or more stars, it is often necessary to filter one of the stars using a dimension that is not shared. When designing a merged fact table to support such comparisons, it is necessary to determine how this dimension will be incorporated. It may be omitted from the merged star, which will limit analytic possibilities, or it may be included in the merged star, which will require that every query constrain on the dimension in question. The sales_goal_facts star at the top of Figure 14-1 tracks several versions of a sales plan. For a given year, there may be a proposed plan, an approved plan, and a revised plan. The plan_version table captures this information. For any given month and territory, there may be three rows recorded in the fact table: one for each version of the sales plan. When you are comparing goals to performance, sales_goal_facts must be constrained to select a single version of the plan. This is done during the first stage of drilling across, as sales_goal_facts is being queried. Failure to do so will cause goal_dollars to be double- or triple-counted. By constraining for a single version of the plan, you can retrieve a single goal_dollars value for each month and territory. These amounts can be safely compared to order_dollars by month and territory in the second stage of the drill-across operation. When building a merged fact table to support the comparison of goals to orders, it will be necessary to decide how to handle plan_version. This dimension is not shared with order_facts. The merged fact table can be designed to select only the most recent plan_ version during the ETL process. The resulting star, however, would only be able to support analysis of performance versus goal for the most recent sales plan. The alternative, as depicted in Figure 14-1, is to include the nonshared plan_version dimension in the merged fact table. Although this dimension does not strictly relate to order_dollars, its inclusion allows the merged fact table to track more than one sales plan. For a given month and territory, there may be two or more rows in the merged fact table one for each plan. During the ETL process, it will be necessary to repeat the order_dollars value for each of these rows. This approach permits goal versus performance analysis using any version of the sales plan. In order to make proper use of this table, it is necessary to select a specific plan_ version in every query. Failure to do so can potentially double-count goal_dollars across multiple plans, and will also double-count the order_dollars. TIP A merged star may contain a nonshared dimension. Queries against the merged fact table must always qualify this dimension for a single value, lest double-counting occur.
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14 Derived Schemas 335
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When a merged fact table contains a nonshared dimension, proper training will be required for anyone who will be developing queries or reports. This requirement should be well documented. Report developers can be taught to constrain the dimension in question every time they build a query, but end users conducting ad hoc analysis may not be counted on to do the right thing. One way to solve this dilemma is to provide end users with a view that constrains the merged fact table in advance. They will have less analytic flexibility but will not produce inaccurate results. Some business intelligence software can be configured to prompt for a constraint automatically whenever the fact table in question is queried.
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