95-797 Data Warehousing
6 units, Carnegie Mellon University
Data warehouses are the central component of a modern data stack. They have solved the problem of analyzing massive amounts of structured semistructured data and are costeffective, performant and easy to use. Data warehouses are the foundation for reporting, ad hoc analysis, business intelligence and machine learning, and enable collaboration among a diversity of users and stakeholders across organizations of all sizes. This class will provide students with the conceptual background and hands on keyboard skills needed to utilize a data warehouse effectively. Throughout the course, students will work on an endtoend development project, building a working data platform for New York City transit data. Using actual taxi, rideshare, bike share and weather data, students will answer realworld analytics questions, such as How does location and time of day affect trip length and How does weather affect transit preferences. By the end, students will be empowered with the tools and techniques needed to take a realworld data project from problem statement to prototype to production.
Prerequisites: 95-703 (min C) or 90-838 (min C) or 90-728 (min C)
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