Insight without relevance is meaningless in Business Analytics. Relevance comes from a deep understanding of the data and the methods used to store and access it. This course enables students to perform complex tasks associated with data in the business environment, from storage to access. Using current Business Analytics database technologies, students will explore the different storage systems and constructs, the use of analytics structures to define data cubes, and the tools used to perform ETL (Extract, Transform, Load) operations on existing datasets to support Business Analytics. An integral part of the course will be a project in which students will build and demonstrate a fully integrated analytical model—from entering data into an existing Relational Database Management System (RDBMS) and using ETL tools to get relevant data into the analytical database (cube), to running analytical queries on the cube to provide meaningful insight into the data.