The Value of Data Warehouses and Data Lakes
For decades, organizations have recognized the need to perform analyses that draw upon information from various parts of an organization. Product profitability analyses require production costs, selling costs and customer service costs. Financial plans require sales information, operational information, marketing information and workforce information. Bringing these diverse sources of information together makes it easier to perform rich analyses on consistent sets of information, so data warehouses have long been a foundational component of enterprise information architectures. As the collection and storage of big data has become standard for many organizations, the concept of consolidating data into a central repository has been extended to include the creation of data lakes.