DATA TECHNOLOGY FOR BUSINESS ANALYTICS

Prerequisites & course information

Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Extract data from both structured or unstructured databases Audience: Graduate 2. Transform and combine data with other relevant information and load into targeted systems such as data warehouses, data marts or analytical applications Audience: Graduate 3. Use Python to execute simple web scraping, mine data from social networks, and use the libraries for advanced data analysis beyond simple descriptive analytics Audience: Graduate 4. Implement Online Analytical Processing (OLAP) and create multi-dimension data cubes Audience: Graduate 5. Execute social mining techniques and create valuable information from text-mining for decision-making Audience: Graduate 6. Discuss current landscape in data warehousing, big data, and other emerging topics Audience: Graduate Learning Outcomes: 1. Extract data from both structured or unstructured databases Audience: Graduate 2. Transform and combine data with other relevant information and load into targeted systems such as data warehouses, data marts or analytical applications Audience: Graduate 3. Use Python to execute simple web scraping, mine data from social networks, and use the libraries for advanced data analysis beyond simple descriptive analytics Audience: Graduate 4. Implement Online Analytical Processing (OLAP) and create multi-dimension data cubes Audience: Graduate 5. Execute social mining techniques and create valuable information from text-mining for decision-making Audience: Graduate 6. Discuss current landscape in data warehousing, big data, and other emerging topics Audience: Graduate