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Unfortunately, this constraint will not pick up Hal Smith. His tax exempt status is NULL, which is neither equal nor unequal to the string Tax Exempt. The correct way to deal with NULLs in SQL comparisons is to use IS NULL or IS NOT NULL comparisons. To find people who do not have a tax exempt status, this might look like:
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PART III
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TIP Do not allow the storage of NULLs in dimension columns. Instead, choose a value that will be used whenever data is not available. Rather than store NULLs in a dimension, star schema designers choose specific values that will be used when a data value is not available. For text columns, the value N/A is a trusted standby. For numeric columns, the value 0 is usually chosen, and dates are often defaulted to an arbitrary date in the very far future (more on dates in a moment). Sometimes, a series of different values is used. In some cases, developers choose to use multiple values that describe why source data is unavailable, such as Unknown and Invalid. Note that while these values lift away the complications of testing for NULLs, they are still objectionable from a theoretical standpoint. Technically speaking, these are not values, but information describing the reason for a lack of a value. In cases where questionable or missing data is expected in a specific column, designers may introduce an additional column to describe the status of the column. For example, our tax_exempt_status column may be supplemented by one that indicates valid_tax_exempt_ status, taking on the values Valid and Invalid.
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Sometimes, it is not possible to associate a fact with a row in a dimension table. This occurs when the dimension value is unknown or invalid, or the relationship is optional. In an ER model, the traditional solution is to store a NULL value in the foreign key column. Unfortunately, the presence of NULL foreign keys in a fact table leads to more analytic complications. Entire fact table rows disappear from query result sets, unless one makes use of outer joins. Employing an outer join causes query results to contain NULLs, even if dimension tables do not. An example of an optional relationship occurs in retail sales. You may have noticed that in some stores the cashier will note when a salesperson has helped you. This information may be used to evaluate salespeople or to compute their compensation. Whatever the reason, some sales have an associated salesperson, while some do not. The star schema in Figure 6-9 accommodates this optionality by allowing the salesrep_key to be NULL. Like the NULL value in a dimension column, this approach will lead to problems when formulating queries. The workaround tactics explored for NULL values in dimension columns will not suffice. Additional workarounds will be required. Notice that there are types of salesreps and that some are managers. Managers may have special flexibility when it comes to pricing, so perhaps someone has asked for a report covering sales in which managers were not involved. A well-meaning developer might mistakenly write a query like this:
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SELECT store.store_name, sum(sales_facts.quantity_sold) FROM store, salesrep, sales_facts
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6 More on Dimension Tables 135
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WHERE salesrep.salesrep_type <> 'Manager' AND salesrep.salesrep_key = sales_facts.salesrep_key AND store.store_key = sales_facts.store_key GROUP BY store.store_name
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Unfortunately, this SQL query will not pick up all sales where a manager was not involved. For fact table rows where there is no salesperson, the join to the salesrep dimension fails altogether; such facts will not be included in the query results. This occurs because the NULL foreign key cannot be matched to a row in the dimension table. The only way to produce the desired results is to employ an outer join. An outer join instructs the DBMS to include rows from one table, even if it is being joined to another table that does not include a corresponding row. If a corresponding row is not found, the database will generate NULL values for its columns in the result set. So, for example, when the fact table in Figure 6-9 is outer-joined to salesrep, the fact table row with a NULL salesrep_key is given a salesrep_name and salesrep_type of NULL. This means that the previously discussed tactics for
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