Business Analytics: Building Business Intelligence in a Data-Driven World
- Business data management process and business analytic approaches
- Experiential project management using live data sets for analysis and application
- Data management, including:
- data mining, marketing technology, applied statistics
- how to interpret and communicate data analysis
- the ethical and intellectual property issues related to data analytics
ITM 818 Introduction to Business Analytics (3 cr)
How digitized business processes and data analytics are essential to the performance and competitive advantage of a modern corporation. Different approaches for strategic data management and business analytics. Real-world cases of successes and failures with analytics-based business strategies.
ITM 822 Project Management (3 cr)
Management of information systems projects. Modeling of business processes. Management of project scope, time, and costs. Planning and control of projects. Program and portfolio management. Consulting issues for effective project management.
CSE 891 Computational Techniques for Large-Scale Data Analysis (3 cr)
Emerging issues in big data (e.g., collection, warehousing, preprocessing and querying; mining, cluster analysis, association analytics; MapReduce, Hadoop; out-of-core, online, sampling-based, and approximate learning algorithms; model evaluation and applications, etc.).
Recommended background: CSE 232 or permission of instructor.
MGT 805 Communications Strategies for Analytics (3 cr)
Development of managerial level business communication skills. Communication strategy development in oral and written form.
STT 863 Applied Statistics Methods (3 cr)
Application of regression models including simple and multiple regression, model diagnostics, model selection, one and two-way analysis of variance, mixed effects models, randomized block designs, and logistic regression.
Recommended background: STT 442 or STT 862; MTH 415 or concurrently.
MKT 829 Marketing Technology and Analytics (3 cr)
The collection and analysis of information from the web, including web-based surveys, web analytics, online communities, blog scraping, and web spiders to support marketing planning and performance. Online
STT 890 Statistical Problems (3 cr)
Individualized study on selected problems.
Or AEC 891 Topics In Agricultural Economics (3 cr)
Or CSE 890 Independent Study (3 cr)
Or any 890-891 independent study/topics course at MSU for analyzing big data problems
CSE 881 Data Mining (3 cr)
Techniques and algorithms for knowledge discovery in databases, from data preprocessing and transformation to model validation and post-processing.
Recommended background: Programming skills in C, C++, Java, and Matlab. Basic knowledge in calculus, probability and statistics.
MKT 865 Emerging Topics in Business (3 cr)
Perspectives on new and emerging issues of business administration. Topics vary including content resource management systems, data mars, software meeting commercial standards, and a firm project related to big data.
ITM 888 Capstone: Business Analytics (3 cr)
Practicum in the development and delivery of predictive data analysis for strategic decision making in organizations. Application of the principles and tools of analytics to real-world problems in R&D, marketing, supply chain, accounting, finance and human resources management. Development and presentation of analytical
insights and recommendations.
MGT 805 Ethics and Intellectual Property Issues (1.5 cr)
Legal, ethical, and intellectual property issues related to big data analytics.
GPA Requirements. Students must maintain a cumulative grade-point average of 3.0 or higher in all graduate courses.