Master of Science in Business Analytics

The Master of Science in Business Analytics at the University of Miami's Miami Herbert Business School is designed for students who want to turn data into meaningful business insights and use analytical techniques to support strategic decision-making. The program combines business knowledge, statistics, programming, predictive modeling, and machine learning to prepare students to address complex business challenges across industries.

Students learn how to analyze large datasets, identify patterns, predict consumer behavior, and forecast business performance. These skills are increasingly valuable to organizations that rely on data to improve efficiency, understand customers, manage risk, and identify growth opportunities.

The program offers two study options: a 10-month full-time Regular Track and a two-year part-time Professional Track designed for working professionals. This flexibility allows students to select a pathway that fits their educational and career goals.

A key strength of the program is its practical focus. Alongside technical coursework, students develop communication and problem-solving skills and complete a business analytics capstone project connected to real-world organizational challenges. The curriculum also offers elective choices in areas such as marketing analytics, supply chain analytics, accounting analytics, cloud technologies, and AI-powered product management.

This program is particularly suitable for students interested in business intelligence, data analysis, predictive analytics, marketing research, financial analytics, operations, and data-driven management.

Curriculum Structure

The curriculum combines programming, statistical analysis, predictive modeling, business decision-making, and applied projects. The following stages provide a useful overview of how these subjects build on one another; they are a thematic summary rather than the university's official semester sequence.

Initial Stage: Analytical and Technical Foundations

Students begin by developing the technical and quantitative skills needed to work with business data.

Core courses include:

• BTE 601 – Python Programming: Introduces programming techniques used to analyze data and solve business problems.

• MAS 631 – Statistics for Managerial Decision Making: Develops statistical knowledge for interpreting evidence and supporting managerial decisions.

• MAS 632 – Management Science Models for Decision Making: Examines quantitative models that help organizations evaluate alternatives and make informed decisions.

• MAS 639 – Data Acquisition and Preparation: Focuses on obtaining, organizing, and preparing data for analysis.

• BUS 610 – Executive Problem Solving: Critical Thinking Strategic Communication: Develops critical thinking and communication skills for explaining analytical findings and recommendations.

These subjects help students establish a foundation in programming, quantitative reasoning, data preparation, and business problem-solving.

Middle Stage: Predictive Analytics and Machine Learning

Students progress to advanced analytical methods that help organizations understand trends, forecast outcomes, and make data-driven decisions.

Key courses include:

• MAS 637 – Applied Regression Analysis I: Introduces regression techniques for identifying relationships between variables and analyzing business outcomes.

• MAS 646 – Applied Regression Analysis II: Extends regression analysis to more advanced modeling applications.

• MAS 640 – Applied Time Series Analysis and Forecasting: Explores methods for analyzing data over time and forecasting future trends.

• MAS 648 – Machine Learning for Data Analytics I: Introduces machine learning methods for extracting insights and developing predictive models.

• MAS 649 – Big Data Analytics: Examines techniques for analyzing large datasets and identifying useful business information.

• MAS 651 – Machine Learning Methods for Artificial Intelligence: Covers machine learning approaches used in artificial intelligence and advanced analytics.

These courses help students develop the ability to interpret data, build predictive models, forecast business performance, and support strategic decisions using analytical evidence.

Advanced Stage: Specialization and Applied Learning

In the advanced stage, students select electives aligned with their interests and apply their knowledge through a capstone project.

Examples of elective courses include:

• ACC 628 – Introduction to Accounting Analytics: Applies analytical methods to accounting information and financial data.

• BTE 612 – Cloud Technologies: Explores cloud technologies and their relevance to modern business systems.

• BTE 623 – Database Management Systems: Develops an understanding of database systems used to store, organize, and manage information.

• BTE 646 – AI-Powered Product Management: Examines the use of artificial intelligence in product management and development.

• MAS 627 – Programming for Data Analytics: Develops programming skills for analytical applications.

• MAS 636 – Dashboard Tools for Visual Analytics: Focuses on presenting information through visual dashboards.

• MAS 638 – Business Analytics Consulting: From Basics to AI: Explores analytical consulting approaches and their business applications.

• MGT 642 – Supply Chain Analytics: Applies analytics to supply chain planning and operations.

• MKT 675 – Marketing Analytics: Uses data to support marketing decisions and evaluate customer behavior.

The MAS 652 – Business Analytics Capstone Project is a required component. Students work on an approved project developed in collaboration with faculty and industry partners, applying analytical methods to a real organizational challenge.

The program requires 33 credit hours, with required courses and electives forming the overall curriculum. Elective availability may vary according to student demand.

Focus Areas

The program's curriculum supports several areas of business analytics and data-driven decision-making.

• Business Intelligence and Data Analysis: Learn to organize, interpret, and communicate business data to support organizational decisions.

• Predictive Analytics and Forecasting: Develop models to estimate future demand, revenue, expenses, and other business outcomes.

• Machine Learning and Artificial Intelligence: Explore computational methods that help identify patterns, automate analysis, and improve predictions.

• Big Data Analytics: Develop skills for working with large and complex datasets.

• Marketing Analytics: Analyze customer behavior, evaluate marketing performance, and support customer-focused strategies.

• Financial and Accounting Analytics: Use analytical methods to interpret financial information and support business planning.

• Supply Chain Analytics: Apply quantitative techniques to operational planning, logistics, and supply chain performance.

• Data Visualization: Present analytical results through dashboards and other visual tools that help stakeholders understand complex information.

• Business Analytics Consulting: Apply analytical techniques to business problems and develop evidence-based recommendations.

• Database and Cloud Technologies: Understand the systems and technologies used to manage and process business data.

Students can use elective choices to emphasize areas that match their interests and career objectives.

Learning Outcomes

Graduates of the Master of Science in Business Analytics can develop the ability to:

• Acquire, prepare, organize, and visualize business data.

• Use Python and other analytical tools to support data-driven decisions.

• Apply statistical methods to evaluate business problems.

• Build and interpret predictive models.

• Analyze historical data and forecast future business outcomes.

• Apply machine learning techniques to business and analytical challenges.

• Work with large datasets to identify trends and useful insights.

• Communicate analytical findings to both technical and nontechnical audiences.

• Use quantitative models to evaluate alternatives and support management decisions.

• Apply analytics to marketing, finance, accounting, and supply chain management.

• Collaborate with others to solve practical business problems.

• Integrate analytical results into recommendations that support organizational goals.

• Apply classroom knowledge to an approved capstone project.

The program combines technical training with business communication and applied problem-solving, helping students translate analytical findings into practical recommendations.

Professional Alignment (Accreditation)

The Master of Science in Business Analytics is offered by Miami Herbert Business School at the University of Miami. The curriculum combines quantitative analysis, programming, business decision-making, and applied analytics to prepare students for roles that require both technical expertise and business understanding.

The program is STEM-designated, according to the school's published program brochure. For eligible international students in the United States, STEM designation may allow an application for an extension of Optional Practical Training (OPT), subject to applicable immigration rules and individual eligibility. Students should confirm the program's current STEM classification and their eligibility with the university and the relevant immigration authorities.

The degree emphasizes practical analytical skills that are relevant to employers across industries, including finance, consulting, technology, retail, healthcare, marketing, and logistics. Applicants should consult the current official academic bulletin for the latest curriculum and admission requirements.

Reputation and Employability

Miami Herbert Business School offers specialized graduate business programs designed to help students develop focused professional skills. The Master of Science in Business Analytics combines technical training with business applications, giving students opportunities to explore how analytics can improve organizational performance and decision-making.

The program's Python, statistics, regression analysis, forecasting, machine learning, and big data coursework can help students build skills relevant to employers seeking professionals who can interpret data and communicate actionable insights.

Potential career pathways include:

• Business Analyst: Evaluate business processes and recommend improvements using data.

• Business Intelligence Analyst: Develop reports, dashboards, and insights to support management decisions.

• Data Analyst: Organize and interpret datasets to identify trends and answer business questions.

• Business Analytics Consultant: Help organizations address operational and strategic challenges through analytical methods.

• Marketing Analyst: Analyze customer behavior, campaign performance, and market trends.

• Financial Analyst: Use quantitative information to evaluate financial performance and support planning.

• Operations Analyst: Identify opportunities to improve efficiency, resource allocation, and business processes.

• Supply Chain Analyst: Apply data analysis to inventory, logistics, and supply chain performance.

• Forecasting Analyst: Develop models to estimate demand, revenue, and other business outcomes.

• Analytics Specialist: Apply statistical and machine learning methods to business problems.

• Product Analytics Analyst: Use data to understand product performance and inform product decisions.

• Risk Analyst: Evaluate data to identify and assess potential business or financial risks.

These are potential career directions rather than guaranteed outcomes. Actual opportunities depend on a graduate's technical proficiency, prior experience, internships, communication skills, and employer requirements.

The program's capstone project offers an opportunity to apply analytical methods to an approved real-world business problem. This experience can help students demonstrate practical problem-solving skills when pursuing internships or full-time positions.

For students who want to combine technical analytics skills with business knowledge, the University of Miami's Master of Science in Business Analytics provides a focused pathway into data-driven decision-making. Its flexible full-time and part-time options, specialized electives, and applied capstone make it worth considering for students preparing for careers in analytics, consulting, finance, marketing, and operations.