The concept of the Data Warehouse emerged in the 1980s as technology enabled organizations to integrate data from a range of sources into a common data model. Integrated data promised to provide insight into operational processes and open up new possibilities for leveraging data to make decisions and create organizational value. As importantly, data warehouses were seen as a means to reduce the proliferation of decision support systems (DSS), most of which drew on the same core enterprise data. The concept of an enterprise warehouse promised a way to reduce data redundancy, improve the consistency of information, and enable an enterprise to use its data to make better decisions.

Data warehouses began to be built in earnest in the 1990s. Since then (and especially with the co-evolution of Business Intelligence as a primary driver of business decision-making), data warehouses have become ‘mainstream’. Most enterprises have data warehouses and warehousing is the recognized core of enterprise data management.63 Even though well established, the data warehouse continues to evolve. As new forms of data are created with increasing velocity, new concepts, such as data lakes, are emerging that will influence the future of the data warehouse. See Chapters 8 and 15.

The primary driver for data warehousing is to support operational functions, compliance requirements, and Business Intelligence (BI) activities (though not all BI activities depend on warehouse data). Increasingly organizations are being asked to provide data as evidence that they have complied with regulatory requirements. Because they contain historical data, warehouses are often the means to respond to such requests. Nevertheless, Business Intelligence support continues to be the primary reason for a warehouse. BI promises insight about the organization, its customers, and its products. An organization that acts on knowledge gained from BI can improve operational efficiency and competitive advantage. As more data has become available at a greater velocity, BI has evolved from retrospective assessment to predictive analytics.