Overview of Data Warehousing and OLAP
The increasing processing power and sophistication of analytical tools and techniques have resulted in the development of what are known as data warehouses. These data warehouses provide storage, functionality, and responsiveness to queries beyond the capabilities of transaction-oriented databases. Accompanying this ever-increasing power is a great demand to improve the data access performance of databases. As we have seen throughout this book, traditional databases balance the requirement of data access with the need to ensure data integrity. In modern organizations, users of data are often completely removed from the data sources. Many people only need read-access to data, but still need fast access to a larger volume of data than can conveniently be downloaded to the desktop. Often such data comes from multiple databases. Because many of the analyses performed are recurrent and predictable, software vendors and systems support staff are designing systems to support these functions. Presently there is a great need to provide decision makers from middle management upward with information at the correct level of detail to support decision making. Data warehousing, online analytical processing (OLAP), and data min-ing provide this functionality. We gave an introduction to data mining techniques in Chapter 28. In this chapter we give a broad overview of data warehousing and OLAP technologies.
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