The first part of the course discusses Data Warehousing as one of the main mechanisms for practical storage of historical data derived from the enterprise operational databases. Several models for organizing and re-factoring databases along various dimensions, as used in Data Warehouses, are discussed, and justified. Data warehouses represent just one, but perhaps the most readily available source of data within an enterprise, for performing data mining. Additional data sources for mining are discussed, including governmental and commercial sources. The second and third parts of the course discuss Data mining and Data Warehousing tasks, techniques and the tools that implement these. Major data mining tasks include classification, clustering and diagramming. These generic tasks are supported through a set of techniques that include decision trees, self-organizing maps, neural networks, and other visual representation techniques. The most representative commercial tools for data mining incorporating these techniques will be used by students to mine some publicly available data sets and report their findings.