Data Integration for Analytics (formerly "Data Warehousing") explores all the ways that modern data are integrated, transformed, modeled, and stored to support Data Analytics and Data Science. Specific course topics include: Traditional Data Warehouses, Data Lakes, and In-Memory Databases. Emphasis is placed on developing systems, skills, and strategies to create a comprehensive analytics environment that supports: Data Analytics, Data Mining/Predictive Analytics, Prescriptive/Preemptive Analytics, Geographic/Location Analytics, Real-Time Analytics, Social Media Analytics, Sentiment Analytics, and Big Data Analytics. This course is delivered using readings, discussions, video demonstrations, and hands-on software projects.