MKTG 630: Predictive Analytics & Data Mining
Prerequisites: MBA Status or permission from instructor
Credit hours (3)
This course, the second Business Analytics course taken by MBA students, provides
an in-depth understanding and application in Predictive Analytics and Data Mining
techniques in order to solve strategic business problems.
Detailed Description of Course
This course, provides an in-depth understanding and application in Predictive Analytics
and Data Mining techniques in order to solve strategic business problems. The course
will provide MBA students with an in-depth understanding and application in Predictive
Analytics and Data Mining and their extensive use of analytical reasoning and statistical
and quantitative analysis. Exploratory and predictive analytics in providing fact-based
models to assist management in making decisions and determining appropriate actions
will be emphasized.
Detailed Description of Conduct of Course
Contemporary background readings from texts, contemporary articles from industry leaders
and journal articles will provide the foundational knowledge of the various predictive
analytics and data mining techniques. Applied exercises and projects will be used
to provide students with an understanding of applications of Data Mining and Predictive
Analytics to managerial decisions using 鈥渂ig鈥� data through hands-on use of industry
standard and emerging analytic tools and software including: forecasting and optimization
algorithms; pattern recognition modeling; partitioning, hierarchical and linkage cluster
based segmentation procedures; classification and decision trees procedures; neural
networks; multiple regression; logistical regression; discriminant analysis; and factor
analysis. Central to student learning is the realization that data mining is not
just about numerical data, as 80% of the world鈥檚 data is unstructured, comprised of
text, emails, photos, etc. Student will learn the tools and techniques to make sense
of both numerical, text, and other unstructured data.
Goals and Objectives of the Course
In completing this course student will:
鈥� Recommend the appropriate Predictive Analytics and Data Mining techniques for a
variety of business decision problems
鈥� Apply the processes of Predictive Analytics and Data Mining for formulating business
objectives, data selection, preparation, and partition to successfully design, build,
evaluate and implement analytic models for a variety of practical business applications
鈥� Analyze large datasets typical in today鈥檚 corporate setting with using IBM SPSS
advanced Data Mining software
鈥� Apply predictive models such as classification and decision trees, neural networks,
regressions, association analysis, and link analysis, to typical corporate Big Data
鈥� Interpret analyses produced by advanced analytical procedures and explain the results
to better inform management decision-making
Assessment Measures
Assessment measures may include but are not limited to applied assignments, applied
projects, and examinations.
Other Course Information
None
Review and Approval
December 6, 2017
December 10, 2013