Required courses will be taught with modern data analytics programming languages and tools, e.g., SQL, Hadoop, SAS, R, Python, Excel-based add-ins, etc.
BAN 610 Database Management and Applications (3)
- Data modeling, database design and implementation, database administration, and database applications. Topics include: database design, incorporating business rules into entity-relationship (ER) models, transformation of an ER model into a relational database design, normalization of database tables, and SQL languages. Prerequisites: Post-baccalaureate standing. A-F grading only.
BAN 612 Data Analytics (3)
- Data collection, preparation, visualization, and analysis with software applications. Topics include: web scraping, Application Program Interface (API) data collection, data wrangling, visualization, data type and structure, and computational and quantitative methods. Prerequisites: BAN 601 and BAN 602. A-F grading only.
BAN 620 Data Mining (3)
- Course introduces the fundamental concepts of data mining and provides extensive hands-on experience in applying the concepts to real-world applications. Topics include dimension reduction, classification, association analysis, clustering and model evaluation techniques. Business applications of data mining techniques are emphasized. Prerequisites: BAN 602. A-F grading only.
BAN 622 Data Warehousing and Business Intelligence (3)
- Data warehousing and business intelligence concepts, design, implementation, and software tools. Topics include data warehouse architecture, dimensional model design, data integration and visualization, business intelligence reporting and dashboards. Prerequisites: BAN 610. A-F grading only.
BAN 630 Optimization Methods for Analytics (3)
- Determining the best solution among various choices, suggesting decision options, and illustrating the implications of each option. Topics include: optimization methods, queuing models, simulation, and application-based software. Prerequisites: Post-baccalaureate standing. A-F grading only.
BAN 632 Big Data Technology and Applications (3)
- This course covers key technologies and applications for big data analytics. Topics include: distributed file systems, big data input/output, streaming technologies, techniques for parallel processing, and big data application development. Prerequisites: BAN 601 and BAN 602. A-F grading only.