An Introduction To Data Warehousing

Figure 10 illustrates the analysis processes that run against a data warehouse. Although a majority of the activity against today’s data warehouses is simple reporting and analysis, the sophistication of analysis at the high end continues to increase rapidly. Of course, all analysis run at data warehouse is simpler and cheaper to run than through the old methods. This simplicity continues to be a main attraction of data warehousing systems.

Summary This paper introduced the fundamental concepts of data warehousing. It is important to note that data warehousing is a science that continues to evolve. Many of the design and development concepts introduced here greatly influence the quality of the analysis that is possible with data in the data warehouse. If invalid or corrupt data is allowed to get into the data warehouse, the analysis done with this data is likely to be invalid. After the rapid acceptance of data warehousing systems during past three years, there will continue to be many more enhancements and adjustments to the data warehousing system model. Further evolution of the hardware and software technology will also continue to greatly influence the capabilities that are built into data warehouses. Data warehousing systems have become a key component of information technology architecture. A flexible enterprise data warehouse strategy can yield significant benefits for a long period.