barcode vb.net 2010 Using the Accumulating Snapshot in Software

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Using the Accumulating Snapshot
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Constructed in this manner, the accumulating snapshot is a useful and powerful tool for studying time spent at any processing stage or any combination of stages. Elapsed days can be studied in terms of their minimums, maximums, or averages across any relevant dimensions, simply by aggregating the appropriate facts as required. No correlated subquery is necessary. For example, the average processing time for applications that were processed in January 2009 can be determined with a simple SQL statement:
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SELECT avg( days_processing ) FROM mortgage_processing_facts, day WHERE mortgage_processing_facts.day_key_processed = day.day_key aND day.month = "January" aND day.year = 2009
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Similarly, the average time spent reviewing and processing an application is easily computed:
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SELECT avg( days_reviewing + days_processing ) FROM mortgage_processing_facts, day aS day_processed WHERE mortgage_processing_facts.day_key_processed = day_processed.day_key aND day_processed.month = "January" aND day_processed.year = 2009
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Queries like these can be further embellished, for example by grouping results by a particular processor, customer characteristic, or application characteristic. In all cases, a correlated subquery is not required. TIP An accumulating snapshot design can measure time spent at various processing stages. One row is recorded for each instance of the entity on which the process operates. This row will have multiple day keys that refer to the date of entry into each status, and facts that will accumulate the number of days spent in each status. These facts can be aggregated or averaged across various dimensions to study the efficiency of the various processing stages. Averages are not the only option. Queries may look for minimum or maximum values, using the SQL MIN() and MaX() functions. Some reports may list the number of applications that spend more than a certain amount of time at a stage, making use of the COUNT() function in conjunction with a WHERE clause, as in COUNT(*) WHERE days_processing > 5. The accumulating snapshot is an effective vessel for recording facts that describe elapsed time at various processing stages and enabling powerful reporting capabilities. Of course, the story does not end here. A variety of additional considerations should be reviewed when building an accumulating snapshot.
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Accumulating Snapshot Considerations
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As with the periodic snapshot, the accumulating snapshot is not a replacement for the transaction model. In many cases, the two will complement each other nicely. Sometimes, the major milestones of interest when measuring elapsed time do not correspond directly to individual statuses, but instead summarize them. In other cases, the operational process may not be a standard linear progression. In still other cases, separate operational systems may track different elements of status. These complications can all be overcome but will increase the ETL complexity. Finally, it is important to consider the impact of slowly changing dimensions on the accumulating snapshot design.
Pairing Transaction and Accumulating Snapshot Designs
The accumulating snapshot is a useful tool for studying the elapsed time spent at one or more processing steps. Keep in mind, though, that this is not the only way to study a process. Other forms of analysis are better suited to a transaction model like the one in Figure 11-5. Common examples include the reporting of numbers of items processed at various stages, studying workloads, and the analysis of process patterns. When the design for a business process includes both a transaction star and an accumulating snapshot, the accumulating snapshot should use the transaction star as its source. This step ensures consistency across the two stars, both in terms of the activities they represent and in terms of the representation of dimensional detail. As an alternative to sourcing both stars to an operational system (or enterprise data warehouse in a Corporate Information Factory architecture), this approach also simplifies the ETL processing and eliminates some redundancy. TIP Transaction and accumulating snapshot models complement each other nicely. The accumulating snapshot allows the study of elapsed time at processing stages, while the transaction model allows analysis of the steps themselves. If both are built, design the accumulating snapshot to use the transaction star as its source.
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