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Master of Business Analytics

MBAN 2024-2025 Curriculum

The master's in business analytics program can be completed in 12 months. The curriculum explores every step of the data analysis and insight generation process, from collecting, cleaning and analyzing data to communicating and getting buy-in on data-based business decisions in your organization.

The core curriculum comprises intensive analytics courses that teach the mathematical and programming skills you need to adapt to any analytics software. Other courses provide training in business intelligence, business problem definition and communication of analysis results. The program culminates with a capstone project in which you will consult with real business leaders to analyze their data and recommend a solution to a business problem they are facing.

 MBAN terms are 11-week quarters with term starts in April and July.  Beginning with Fall 2025, the MBAN program will be offered on the semester format with terms beginning in August (Fall), January (Spring) and Summer (May).  

Foundations of Analytics (all required)
Statistical Analysis for Business Decisions (BAN 611, 1.5 credits)

This course is an introduction to descriptive and inferential statistics for MBA students. The overall purpose is for
students to develop skills in:

  • Describing/summarizing sample data sets
  • Using probability distributions
  • Drawing conclusions about the properties of large groups when only sample information is available
  • Investigating relationships among several properties based on a sample of those properties
Problem-Solving Methods and Tools (MIS 661A, 3 credits)

Overview of organizational decision-making. Problem-solving steps and algorithms. Introduction to programming. Introduction to specialized software for data analytics.

 

Business Analytics (BAN 791, 1.5 credits)

Role of business analytics in providing support for business decisions, particularly an overall framework for analyses involving mathematical models. Emphasis on optimization and descriptive modeling utilizing analysis techniques such as linear programming, integer and binary programming, and simulation modeling. Focus on
application of such techniques to business decisions with cases. Use of spreadsheets to implement analytic models. Prerequisite: BAN 611 or MBA 511

Advanced Analytics (all required)
Introduction to Machine Learning (BAN 614, 3 credits)

Topics include programming in R, data manipulation, and exploratory data visualization; predictive modeling using regression, decision trees, naive bayes, and discriminant analysis; regularization and resampling methods; clustering and principal component analysis. Prerequisites: BAN 611 or MBA 511 and MIS 661A

Advanced Business Analytics (BAN 618, 3 credits)

Techniques for the solution and analysis of various business problems. Types of models: linear programming, integer linear programming, network models, utility theory with risk attitude, dynamic programing, Monte Carlo simulation, and decision tree. Problem-oriented case studies. Emphasis on business insights, implications, and
analysis of the solution procedures. Use of modeling languages, such as Python, and commercial solvers. Prerequisites: BAN 791 or MBA 791 and MIS 661A

 

Data Management for Analytics (MIS 664A, 3 credits)

Phases in creating relational database systems for collecting, storing and extracting data for business analysis, including use of the Structured Query Language (SQL). Data quality issues. Steps in creating and operating a data warehouse, including multidimensional modeling, extracting, transforming and loading data for business analysis. Prerequisite: MIS 661A

Special Topics in Data Analytics (MIS 668A, 3 credits)

Selected advanced business intelligence and data analytics topics, e.g., big data, social network analysis, web (social media) analytics, text analytics, text scraping and others, as applied to business scenarios. Seminar-based or survey-based course. Project intensive. Prerequisites: MIS 661A, MIS 664A, MIS 667A

Organizational Problem-Solving (all required)
Business Analytics – Processes and Techniques (BAN 663, 1.5 credits)

Survey of the main phases of the life cycle of analytics, including information requirements determination; data acquisition; analysis with descriptive, predictive and prescriptive models; visualization; analysis presentation; and delivery. Hands-on practice with creating visualization and dashboards, and with using data-mining tools to analyze data. Prerequisite: BAN 611 or MBA 511

Case Studies in Analytics (BAN 615, 1.5 credits)

Selected cases illustrating the use of various analytics methods in descriptive, predictive and prescriptive analytics to solve specific business problems. Prerequisite: BAN 791 or MBA 791

Advanced Business Intelligence (MIS 667A, 3 credits)

The role of business intelligence in setting and achieving organizational goals. How business intelligence supports different types of organizational decision-making. Tools and analytical methods for acquiring business intelligence, including statistical methods, data mining, visualizations and programming for analytics. Methods and organizational structures for implementing business intelligence in own organization, including maturity assessments, roadmaps and business intelligence excellence centers. Prerequisites: MBA 663A (may be taken as a co-requisite), MIS 661A

Capstone Project in Analytics (BAN 710, 3 credits)

Application of business analytics knowledge and skills with actual firm, student teams, project planning and implementation, and reporting and presenting to firm’s management. Prerequisites: BAN 614, BAN 618, MIS 667A

Electives – Analytics Applications Track (6 credits required)
Supply Chain Analytics (BAN 613, 3 credits)

The course will use analytical tools rooted in mathematics, statistics and predictive modeling to develop insights from transaction and transportation data that can lead to savings, efficiencies and competitive advantage. The course will help the student learn how to cut through supply chain complexity to deliver goods and services efficiently and responsively. Emphasis will be placed on effectively communicating the insight.

 

Project Management for Professionals (BAN 616, 3 credits)

Project-oriented work makes up the bulk of managerial activity in organizations, and, consequently, knowledge of project management principles is valued highly. This course offers a broad review of issues and approaches to contemporary professional project management useful for any MBA student and future manager.

Marketing Analytics (MBA 632, 3 credits)

This course introduces students to common statistical analytical procedures related to marketing decisions. With a focus on interpreting statistical output, students will work with common marketing analytics procedures to understand what insights data can provide into marketing strategy. Readings and cases demonstrate the relevance of analytics principles in real-world situations.

CONTACT

MBAN Program

Anderson
300 College Park
Dayton, Ohio 45469 - 2130
937-229-2938
Email