INFS6730-B Data Integration For Analytics (Fall 2024)
Course Details
Section will be taught totally online with no scheduled class meetings. Students must arrange for daily access to a computer and the Internet prior to the start of classes. Robert Morris labs are to be used only as a backup in special situations and may not be relied upon for extended periods of time. In addition to the Internet link, online classes have a large emphasis on email. All messages from the instructor and other information regarding online classes, including user ids, passwords, and login instructions will be sent to your Robert Morris University email account. Visit http://rmu.blackboard.com/ for more information.
Session, Dates: 4 (10/19/2024 - 12/13/2024)
Days: ONLINE
Time: -
Location: Internet/Online
Room:
Seats Available: No Seats 0 Waiting
Credits: 3
Course Description
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.
Prerequisite: INFS6240 or INFS6242 3 Credits
Prerequisite: INFS6240 or INFS6242 3 Credits
Course Materials
About the Instructor(s)
Farbod Mirzaei, M.S.
mirzaei@rmu.edu
Wheatley Center 142
Profile
Part-Time Faculty
Computer and Information Systems
mirzaei@rmu.edu
Wheatley Center 142
Profile