how to make barcode in vb.net 2010 Considering Mini-Dimensions in Software

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Considering Mini-Dimensions
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Last, it may be possible to isolate a subset of the dimension s attributes and use them as the basis for a new dimension called a mini-dimension. Like a junk dimension, this table s attributes do not represent a single analytic concept. This new dimension table can alleviate size problems at the expense of limited browsability. As the next section reveals, the minidimension can have an unexpected impact on table growth.
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Mini-Dimensions Alleviate eTL Bottlenecks and excessive Growth
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When a dimension table with a large number of rows undergoes a large number of type 2 changes, it can become too large. Constant improvements in DBMS technology may alleviate any concern about table size; 1 million rows may have seemed large a decade ago but is hardly a concern today. Even as advances in storage technology keep pace with a rapidly growing dimension table, it remains necessary to load the table. When an ETL process detects changed source data, it must determine whether it is necessary to apply a type 1 or type 2 change to existing dimension rows. If there are a large number of type 2 attributes, the process of determining how to deal with a change may quickly become a bottleneck. Consider the example of a health insurance company that has over a million outstanding policies. The company tracks, among other processes that relate to policies, premium payments made by its customers. Figure 6-4 shows a payments fact table, which records information each time a customer makes a payment. The dimensions include the date of the payment, the invoice information, the customer making the payment, the insurance product, and the policy. Certain aspects of the policies are relatively consistent, while others change more frequently. The bottom portion of Figure 6-4 illustrates what this means for one particular policy, held by Hal Smith. Over the years, a core set of attributes has remained unchanged his policy number, name, and address but slow changes to another set of attributes have generated numerous new rows. Hal married, altered coverage based on changes in his wife s employment, adjusted his deductible, added coverage for children, and removed it when they reached adulthood. All these changes in coverage details are significant from an analytic perspective and were handled as type 2 changes. This means that each change generated a new row in the dimension.
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POLICY DAY PAYMENT_FACTS INVOICE day_key invoice_key customer_key product_key policy_key . . . (facts) . . . policy_key policy_number policy_holder address marital_status family_size covered_parties spouse_coverage covered_children deductible_amount . . .
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These attributes cause a lot of type 2 changes.
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PRODUCT
POLICY policy_ policy_ key number 12882 12911 13400 14779 14922 18911 40111 40111 40111 40111 40111 40111 policy_ holder address marital_ family_ covered_ covered_ deductible status size parties children _amount Single Married Married Married Married Married 1 2 2 3 3 2 1 1 2 3 3 2 0 0 0 1 1 0 250 250 250 250 500 500
Smith, Hal 113 Random Rd. Smith, Hal 113 Random Rd. Smith, Hal 113 Random Rd. Smith, Hal 113 Random Rd. Smith, Hal 113 Random Rd. Smith, Hal 113 Random Rd.
Figure 6-4 Growth in the policy dimension
If there are over 1 million policies, and most policies undergo at least one change in their coverage each year, this dimension table may quickly go from being manageable to being a nuisance. With a large number of type 2 attributes, each change to a policy may also require extensive evaluation to determine whether a new row must be generated for the dimension table. These problems can be solved by removing some attributes from the dimension table and placing them in an entirely new dimension, called a mini-dimension. This separation of elements can have the miraculous effect of eliminating growth and also reduces the impact on the ETL process.
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