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As the data is loaded into the fact table, each column represents a bucket of information with the time period intelligence built into each column. C_MONTH contains sales for just the current month; C_YTD contains sales for each month in the current year. If the month is October, it contains sales from January through October. Data Integrator has a date generation transform, which generates the time periods needed (quarter, month, year, week, etc.). By using our special functions, we can aggregate fact data to these time periods and load the Fact tables in the warehouse with an appropriate indication of the bucket used. You can also create aggregations that manage running ytd, mtd, qtd fields. You use DI s stateful functions to do this. Many analytic applications that build data marts (including SAP BW s Info Cubes) use this kind of structure. However, if your company designs and builds your own fact tables, the DBA must program this kind of intelligence into the load routines; unlike in OLAP databases, there may be no simple toggle to achieve time period intelligence (although newer data integration tools may assist with this). A robust ETL tool may help with the process. For example, BusinessObjects Data Integrator has a date generation transform that will take an individual date value and create the appropriate year, quarter, and month hierarchies. Data Integrator also includes special functions to load data into fact tables to create running year-to-date measures, month-to-date measures, and so on. Even with an ETL tool, this kind of design requires more disk space and a stronger understanding of best practices in data warehouse designs. DBAs may not have the resources to implement this kind of design or the time. (Show me a DBA who is not overworked and overscheduled!) Recall from the first section in this chapter that dimension groupings such as customer age, income level, and product size are also forms of intelligence. Analyzing data by dimensions is the bread and butter of most businesses. Providing alternative groupings can help reveal
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