MSBA Decision Science Track Curriculum

The MS Business Analytics degree focuses on the exciting and fast-growing field of big data. Designed to teach students how to translate data into strategic business decisions, this robust technical foundation is augmented by specialized decision science courses, including linear and integer programming, optimization, and heuristic methods, preparing you for a data-driven career in strategic decision-making and operational efficiency.

Beyond technical skills, our program emphasizes the strategic aspects of decision sciences. Learn to synthesize data into actionable insights, understanding the implications for business processes, risk management, and strategic planning. You'll graduate with the acumen to guide data-driven decision-making, providing strategic and operational insights that shape business outcomes and drive success.

Gain three critical skills by graduation:

  1. How to capture and analyze complex structured and unstructured data sets
  2. How to develop your intuition about where business value can be found and articulated to leadership
  3. How to deliver quantitative analysis in a format that C-suite executives can understand and use

Curriculum Overview

Summer B Term- 6 credits
(June to July)

Designed as an introduction to Business Analytics, which considers the extensive use of data, methods and fact-based management to support and improve decision making. Business intelligence focuses on data handling, queries and reports to generate information associated with products, services and customers, business analytics uses data and models to explain business performance and how it can be improved. The class will be built on heavy hands-on coding; it will introduce and subsequently involve extensive use of Python.


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Exposes the students to commonly used platforms for statistical and predictive analytics. The class will go into depth of analytics using R before demonstrating the same concepts using SPSS and SAS. Students will learn to analyze large datasets, including textual analytics such as twitter-stream analysis using R.


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Fall Term - 12 credits
(August to December)

This course exposes the students to commonly used platforms for statistical and predictive analytics. The class will go into depth of analytics using Python. Students will learn to analyze large datasets, including textual analytics such as twitter-stream analysis. The class will focus on predictive analytics.


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Explores both the functional and technical environment for the creation, storage and use of the most prevalent source and type of data for business analysis, ERP and related structured data. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, create dashboards, and be source for business intelligence.


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Explores the capabilities and challenges of data-driven business decision making and prepares students to lead in analytics-driven organizations. Introduces a set of common predictive and prescriptive analytics tools. Students apply the analytics tools to important decisions based on practical data sets from various companies. Analytics software packages are used extensively in the course.


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Focuses on formulating decision problems as mathematical models and employing computational tools to solve them. Microsoft Excel is used as the main modeling platform but the course will also cover advanced tools, such as modeling languages. Optimization modeling will be illustrated in problems associated with operations, marketing, management, and finance. Integrates topics from decision analysis and operations management as they relate to modeling management decisions.

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Spring Term - 15 credits
(January to May)

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Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical application and mechanisms for getting this sort of data ready for analytics..


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Forthcoming.

Analyzes key issues related to the design and management of operations and supply chains using quantitative tools such as linear, integer, and non-linear programming, regression, and statistical analysis. Covers important topics such as forecasting, aggregate planning, inventory theory, transportation, risk pooling, production control and scheduling, and facilities location, among others. Uses mathematical modeling, spreadsheet analysis, case studies, and pedagogical simulations to deliver material.


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Covers the concepts and tools to design and manage business processes. Emphasizes modeling and analysis, information technology support for process activities, and management of process flows. Graphical simulation software is used to create dynamic models of business processes and predict the effect of changes. Prepares students for a strong management or consulting career path in business processes.

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In Track-Specific Elective Courses:

MSBC 5680 Optimization Modeling (Fall) Focuses on formulating decision problems as mathematical models and employing computational tools to solve them. Microsoft Excel is used as the main modeling platform but the course will also cover advanced tools, such as modeling languages. Optimization modeling will be illustrated in problems associated with operations, marketing, management, and finance. Integrates topics from decision analysis and operations management as they relate to modeling management decisions.

MBAX 6843 Supply Chain Analytics (Spring) Analyzes key issues related to the design and management of operations and supply chains using quantitative tools such as linear, integer, and non-linear programming, regression, and statistical analysis. Covers important topics such as forecasting, aggregate planning, inventory theory, transportation, risk pooling, production control and scheduling, and facilities location, among others. Uses mathematical modeling, spreadsheet analysis, case studies, and pedagogical simulations to deliver material.

MBAX 6410 Process Analytics (Spring) Covers the concepts and tools to design and manage business processes. Emphasizes modeling and analysis, information technology support for process activities, and management of process flows. Graphical simulation software is used to create dynamic models of business processes and predict the effect of changes. Prepares students for a strong management or consulting career path in business processes.