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Flattening an instance hierarchy poses a few problems. Though none are deal breakers, the utility of a flattened solution is limited. The importance of specific analytic requirements will determine whether flattening is sufficient.

REP CUST ---- ---102 2114

The flattening of an instance hierarchy creates attributes to describe each row s place in a fixed number of levels. One problem with this is that not every row in the table represents the bottom of a hierarchy. For these rows, it will be necessary to decide what values to use for the lower levels. This phenomenon is clearly visible in the example. Not all companies are at the bottom of a four-level hierarchy. Company 1, for example, does not have a corresponding level_2_company, level_3_company, and so forth. So, what values will be used for these columns The usual solution for a member that is not at the bottom of the hierarchy is to backfill its own identity into the lower levels. In Figure 10-4, the shaded cells illustrate backfilled references. This allows a query to group data at any particular level, without losing transactions. So, for example, if we group all orders by level_2_company, we will not miss out on the transactions associated with Company 1. These will still be in our query results. You may choose to use a text string such as Higher Level Company in lieu of backfilling. This makes some reports easier to read but loses the association of higher-level transactions with any specific companies. Backfilling is necessary because flattening an instance hierarchy creates an artificial attribute hierarchy. Just as we could say every product has a brand, every brand has a category, we need to be able to say every company has a level 4 company, every company has a level 3 company, and so forth.

Note that if a database uses multiple files, you can choose to attach or detach one or more of them within the same command. However, if you remove only some of the data files, you might not be able to access all the objects that are part of the database. Table 7-4 provides a summary of the commands and syntax for attaching and detaching databases.

REP CUST ---- ---102 2120

Part IV provides in-depth treatment of advanced features that center on fact tables. It is composed of three chapters. 11: Transactions, Snapshots, and Accumulating Snapshots This chapter covers situations in which a standard transaction-based fact table falls short, and shows how periodic snapshots and accumulating snapshots can be put to use. 12: Factless Fact Tables Sometimes fact tables contain no facts. In this chapter, you will learn about transaction-based factless fact tables, as well as factless fact tables that capture coverage or conditions. 13: Type-Specific Stars This chapter looks at situations where subsets of data have different facts and dimensions, and shows how to make use of core and custom stars for a single process.

An installation of SQL Server 7 assumes the name of the machine onto which it is installed. For example, if my computer is named WORKSTATION1, the name of the SQL Server installation is also WORKSTATION1. So, what happens when the computer name is changed SQL Server 7 does not automatically update its internal settings to reflect the change, and you will receive an error message on startup stating that the SQL Server installation is corrupt. Although the error message might be alarming, you should know that your information is safe. The only problem is that the SQL Server services cannot au-

Any dimensional schema can be supplemented with additional structures that are intended to improve performance or simplify the reporting process. Part V looks at two kinds of supplemental data structures that support high performance. 14: Derived Schemas This chapter teaches you to use derived schemas to provide enhanced performance, simplify report development, or address specific departmental needs. 15: Aggregates This chapter shows how summary tables, or aggregates, can provide powerful performance boosts when implemented wisely.

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