CIS 3252 - Business Intelligence (3)

Data Science cycle, data acquisition, questions and ideal data set, data cleaning, data compliance and security, data sharing, data visualization, data modeling, data analysis and dissemination of results. Storytelling for intelligence dissemination. Data warehousing and on-memory database solutions. Differences and similarities among descriptive analytics, data mining, web analytics and big data. Artificial intelligence and data science. IT governance. Business intelligence, data reporting, digital dashboards. Using data modeling for decision making, business analytics, big data, proprietary and nonproprietary software. Industry cases in marketing, finance, manufacturing, human resources. Future trends of business intelligence. Ethical and privacy issues.

Prerequisite(s): C or better in CIS 2100, and CIS 305 or CIS 3050.
Component(s): Lecture
Grading Basis: Graded Only
Repeat for Credit: May be taken only once
Course Category: Major Elective Course