barcode vb.net 2010 Transactions, Snapshots, and Accumulating Snapshots 289 in Software

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11 Transactions, Snapshots, and Accumulating Snapshots 289
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Accumulating snapshots may also track promised versus actual time that is spent processing an item. 4 of Data Warehouse Design Solutions presents a fulfillment model that does this for a flower delivery business. An accumulating snapshot that tracks the college admissions process can be found in 12 of The Data Warehouse Toolkit. The complex billing life cycle associated with health care services is given the accumulating snapshot treatment by Kimball and Ross in 13 of The Data Warehouse Toolkit. An accumulating snapshot for the claims process in the insurance industry appears in 15 of The Data Warehouse Toolkit. Aggregate Design Snapshots and accumulating snapshots must be evaluated carefully when they are to serve as the source of a summary table or aggregate. These issues are fully explored in 8 of Mastering Data Warehouse Aggregates (Wiley, 2006) by Chris Adamson.
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Part IV
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CHAPTER
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Factless Fact Tables
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In a dimensional design, the fact table is the locus for process measurement. It is the place where measurements are stored. The measurements are called facts, which is where the fact table gets its name. Paradoxically, a fact table does not always require facts to measure a process. A fact table that contains no facts is called a factless fact table. This oxymoron aptly describes the design technique discussed in this chapter. Although no facts are explicitly recorded in a factless fact table, it does support measurement. A factless fact table is useful in two kinds of situations: Factless fact tables for events record the occurrence of activities. Although no facts are stored explicitly, these events can be counted, producing meaningful process measurements. Examples include the number of documents processed or approved, the number of calls to a customer support center, or the number of impressions of an advertisement. Factless fact tables for conditions are used to capture significant information that is not part of a business activity. Conditions associate various dimensions at a point in time. When compared with activities, they provide valuable insight. Examples of conditions include eligibility of people for programs, the assignment of salesreps to customers, active marketing programs for a product, or special weather conditions in effect. This chapter teaches the ins and outs of factless fact table design in each of these situations. You will learn when factless fact tables are necessary, how to design them, and how they are used.
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PART IV
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Fact Table Design
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Events with No Facts
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Sometimes, there appear to be no facts to describe an important business activity. You may be able to define the process, identify fact table grain, and specify numerous dimensions, but find yourself unable to identify any facts. This should not stop you from designing a star schema to track the process. In this situation, you can design a factless fact table. Although it contains no facts, it measures the business activity. Analysis is conducted by counting rows in the fact table. Adding a fact that is always populated with the value 1 can simplify query writing but is not required. Sometimes, if you look closely enough, you may find a fact after all, but a factless design is perfectly acceptable.
Nothing to Measure
For many business processes, the only measurement is the occurrence of events or activities. There are no dollar amounts to be aggregated, no quantities to be summed, no balances to be averaged. Activities are taking place, however sometimes at a breakneck pace. Businesses measure this kind of process simply by counting the activities. Examples of this kind of activity abound. For example: The processing of documents (like contracts or applications) is measured by counting how many are handled by day across a variety of dimensions, including activity (received, reviewed, rejected, etc.), customer, and person doing the processing. Customer support is measured by counting the number of service requests opened, closed, or otherwise processed by representative, customer, product, and problem ticket. Advertisers count the number of impressions, or exposures to an advertisement, across a variety of dimensions. Web site usage is measured by counting page views or interface clicks. Schools and businesses track attendance or absence. You may hear dimensional modelers say no measurements exist for these processes. This is not entirely true: counts are legitimate and important measurements. It just so happens it is not necessary to store a fact to support counting. The fact table may be factless, but the process is measured.
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