CIS 3252W - 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. 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. Industry cases in marketing, finance, manufacturing, human resources. Future trends of business intelligence. Ethical and privacy issues. Writing-Intensive courses must be passed with a C or higher to count towards the University’s 3-unit Writing Requirement.

Prerequisite(s): C or better in CIS 2100, and junior or senior standing.
Grading Basis: Graded Only
Repeat for Credit: May be taken only once
When Offered: As needed; see Academic Department
Course Category: Major Elective Course