Database web hosting - Figure 9-21 also shows three newly added dimensions:
Figure 9-21 also shows three newly added dimensions: LOCATION, TIME, and PRODUCT. Many data warehouse database models include extra dimensions containing information gleaned from the fact tables themselves, and sometimes the dimensions as well. These extra data warehouse-specific type dimensions allow for a better and more efficient structure when separating information in a data warehouse database model: . Locations Locations are usually built from address details, establishing locations for bidders and sellers (for the online auction house) as being in a specific city, state, country, continent, planet, star system, galaxy, and universe. That may seem silly, but you get the point. A location dimension allows analysis of data warehouse information into reports, based on regions. For example, what sells well, in what city, what region, and so on. . Time stamps Time stamp information allows dimensional division of information into time periods. The result is data warehouse reporting that can assess how a company performed in specific periods. For example, reporting could compare profitability in different years, across the same months or quarters. This type of reporting can help to assess the health of a business, among many other things (such as when business should be expected to pick up). If a company has a Christmas rush of trading, they might be able to prepare better for what types of products sell at Christmas, how much they need to manufacture, and where specific products need to be distributed to. . Products Product dimensional information allows division of reporting based on different products, similar to how information and reporting can be divided up into locations and time stamps. There are numerous other data warehouse-specific static information structures. Locations, times, and products are probably the most commonly additional dimensions. Essentially, commonly used dimensions in data warehouse database models (such as locations, times, and products) are generally used all at the same time, in the same reports. Also, data warehouse databases can be become so humongous that serious performance gains can be found by applying reporting filtering using information such as locations, times, and products. Figure 9-22 shows a more detailed star schema for the online auction company data warehouse database model. In Figure 9-22, you can see that the dimensions are still pointing directly, and individually, at all the facts (transactional information). Typically, in a data warehouse, database dimension tables have very few records, relative to the size of fact tables. Fact tables can often rise into the millions, and even billions and trillions of records. Dimension tables containing tens, hundreds, or even thousands of records, and contain relatively much smaller numbers of records than fact tables. This is the idea! 246 Chapter 9
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