how to make barcode in vb.net 2010 Design and Business Intelligence 391 in Software

Generator QR-Code in Software Design and Business Intelligence 391

16 Design and Business Intelligence 391
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ORDER_FACTS day_key product_key customer_key sales_group_key . . . order_dollars . . .
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SALES_GROUP sales_group_key salesrep_key primary_flag SALESREP salesrep_key salesperson_name region . . .
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Expert Configuration Able to produce an impact report Double-counting is possible Novice Configuration Limited to single salesrep per order Avoids possibility of double-counting View: Primary Salesrep ORDER_FACTS day_key product_key customer_key sales_group_key . . . order_dollars . . . SALES_GROUP sales_group_key salesrep_key primary_flag WHERE primary_flag = 'Primary Salesrep' SALESREP salesrep_key salesperson_name region . . .
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Figure 16-9
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Two ways to leverage a dimension bridge table
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In the case of multiple salesreps, the first option can be achieved by grouping the result by salesperson_name. Care must also be taken not to create a grand total with the results, since this would result in a double-count. The second option can be achieved by filtering the query for a single salesrep. The natural key is the best way to accomplish this, but it is also possible to use the salesperson s name. It is not sufficient to constrain on other attributes of salesrep, such as department, since this will select more than one individual. The last option filters the group table for rows where primary_flag contains the value Primary Salesrep. For this to work, every group must have exactly one salesrep flagged as the primary salesrep. This handful of rules may be easy for an experienced developer to follow, but is very likely to be unintelligible to a novice developer, let alone an end user. If steps such as these are not taken, the result can be disastrous. In the example, it can mean a dramatic overstatement of order_dollars. Configuring a business intelligence tool will require preventing users from making such a mistake.
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Part VI
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PART VI
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Tools and Documentation
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The solution, as depicted in the lower half of Figure 16-9, is to provide an option for end users that associates only one salesrep with each order. In the illustration, a view is used to achieve this effect. The view identifies the primary salesrep for each group by joining the bridge to the salesrep table, and filtering on the primary_flag. It may be possible to accomplish the same thing by using the native features of the business intelligence tool in place of the view. An alternative design approach was depicted in 9. The schema in Figure 9-6 stored a primary_salesrep key in the fact table, rather than a primary_flag in the bridge. The end result is the same; novice users are presented with an environment that associates only one salesrep with each order. Expert developers can be provided with a different semantic layer, one that does not contain any such restrictions. Only these users will be able to make use of the bridge to create impact reports. They must be sure to use one of the previously listed techniques, thus ensuring that queries generated by the business intelligence tool do not perform any double-counting.
Attribute Bridge Tables
Like a dimension bridge, an attribute bridge allows a single fact row to be associated with more than one value of a dimension attribute. In this case, the bridge table lies between the dimension and an outrigger, but the effect is the same. The multi-valued attribute, in conjunction with a fact, must be used to group results, filtered for a single instance value, or constrained in such a way as to produce a single value for each instance of the dimension. Figure 16-10 provides an example where each company may participate in numerous industries; one industry will always be designated as primary. Industry must be used to group results, be constrained for a single industry such as Finance, or be limited to one value per company by filtering on the primary_industry column. Since this is a complicated set of rules to expect anyone but an experienced developer to follow, it will be important to construct a semantic layer that prevents the generation of SQL that breaks the rules. This can be done by creating a view of company that includes the primary industry. The view joins the company table, the bridge, and the industry outrigger, constraining on primary_industry. This can be safely joined to the fact table without any concern for double-counting, as shown in the bottom of Figure 16-10. TIP Misuse of a dimension bridge or attribute bridge results in double-counting. If novice users will be using the business intelligence tool, provide a semantic layer that prevents generation of such queries. Experienced users can be given a less restrictive semantic layer that allows use of the bridge to create impact reports. This version will not enforce restrictions; expert users must take steps to ensure that they do not generate inaccurate query results. The dimension bridge and attribute bridge both set up a many-to-many relationship between the bridge and another table. This kind of relationship is often hard for modeling tools to represent, or may make it difficult for a database administrator to declare table relationships. To cope with these situations, bridged designs can be extended to resolve the many-to-many relationship. This is done by establishing a single-column table that has one row for each group, as described in 9. This variation on a bridged design does not eliminate the possibility of double-counting. It will still be necessary to set up a safe query environment for novice users in which generated queries will not double count.
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