Data Warehouse Fundamentals

You know that a data warehouse consists of information derived from multiple business operational systems. It should be distinct from the business operational systems that are used to manage day-to-day business operations. As such, it is optimized for reading rather than for inserting, updating, and deleting records. Although these operations are necessary for any data management system, they are secondary to its primary function as a decision-support store of read-only data. Data population and maintenance is performed offline and as part of an automated, bulk process. The data warehouse is also organized for specialized business information analysis and discovery tools. As such, its design is specifically tailored to work with reporting tools and necessary business reporting metrics. It is used to support (or refute) business plans, directions, and actions.

To achieve BI solution capabilities, corporations have deployed technology to collect raw operational business data from across their business systems. This data is then transformed, cleansed, and merged into specialized collection database models. These processes include applying business-specific rules, defining measures, and defining relationships among data sources. A variety of reporting and analytic applications are then used to view and analyze the data in supporting or refuting business decisions.

In the not-so-distant past, it took a lot of effort and technology to accomplish BI solutions. SQL Server 2005 has enabled corporations to design, deploy, and manage BI solutions with relative speed and ease, all from one integrated technology suite.