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Data Analytics

Analytics, driven by large amounts of data and computing resources, is recognized as a source of value and competitive advantage. Analyzing large data sets, including both structured and unstructured data—often referred to collectively as big data—is becoming a critical basis of competition, underpinning new waves of improved decision making and innovation.  Organizations around the world are struggling to develop the know-how to aggregate, analyze, and monetize the growing surge of available data. The new track – Data Science and Analytics – would provide a strong foundation in technology, statistics, and quantitative modeling that is needed to develop business intelligence and drive organizational decision-making.


Data Analytics Track
Course Description Credits
Required Courses 12
CIS 3100 Object-Oriented Programming I 3
CIS 3120 Programming for Analytics 3
CIS 3400 Database Management Systems I 3
CIS/STA 3920 Data Mining for Business Analytics 3
CIS 4400 Data Warehousing for Analytics 3
Elective Courses 12
Choose four (4) courses of 3 credits each from the following, at least one of which should be a CIS course and one should be a STA course or an OPR course.
CIS 3100* Object-Oriented Programming I 3
CIS 3120* Programming for Analytics 3
CIS 3150 Introduction to Semantic Technologies 3
CIS 3710 Business Intelligence 3
CIS 4170 Data Visualization 3
STA 3154 Business Statistics II 3
STA 3155 Regression and Forecasting Models for Business 3
OPR 3450 Quantitative Decision Making for Business I 3
OPR 3451 Quantitative Decision Making for Business II 3
MKT 4123 Marketing Web Analytics and Intelligence 3
MKT 4561 Marketing Analytics 3
* If you have used one of these programming courses as a required course, you may use the other as an elective.

Faculty Advisor: Prof. Radhika Jain (