Data models are the blueprints of the data in a warehousing environment.
Without data models, both implementation and maintenance of the data warehouse are difficult, if not impossible. Warehouse data modeling presents new issues, complexities, and challenges from those of modeling of OLTP data. When first modeling for the warehouse, even the most experienced of application data modelers will experience these challenges. Different roles and uses of data, changing uses of normalization, and new modeling constructs that focus on time, location, and dimensional aspects of data are among the reasons that warehouse data modeling demands different skills, perspectives, and techniques. This course focuses on where data models fit into a data warehousing process and on the skills needed and the techniques used to produce the models.