Master of Science in Business Analytics

In a global economy that is driven by data, the University of Redlands Master of Science in Business Analytics (MSBA) degree teaches business professionals how to gather and analyze data; create meaningful insights; and make strategic, ethical decisions that enhance organizational value.

Why an MSBA at Redlands

The Master of Science in Business Analytics degree from the University of Redlands School of Business is designed for working professionals who can complete the program in 18 months by taking one of nine courses every eight weeks year-round. We do not require any prerequisites, and applicants do not have to hold an undergraduate degree in a STEM major.

The MSBA degree program zeroes in on specialized areas of business analytics, with an emphasis on information, statistics, big data, predictive & prescriptive analysis, and emerging technologies. Our curriculum is distinctive in that it blends business courses with those in GIS, MIS, IT, and analytics to provide a holistic approach to this business discipline.

The program leverages the University’s strong partnership and Spatial Business Initiative with global mapping giant Esri to provide students with location analytics expertise, case studies, research, and business connections.

The program integrates elements of leadership, ethics, and business/organizational foundational knowledge with technical knowledge and skills in order to arm graduates with the necessary tools to solve business problems and create new business opportunities effectively and efficiently.

Graduates of the program will be business intelligence analysts who can effectively liaison between technical experts and business/organizational users of business analytics, while understanding the ethical and legal aspects of analytics work.

M.S. in Business Analytics Course Sequence

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Program learning outcomes

Upon successful completion of the program, graduates will be able to:

Application of Business Analytics Knowledge

Formulate and scope organizational problems by applying the principles of business, analytics, and information systems.

Use appropriate data and analytical methods to improve decision-making throughout an organization’s value chain.

Communication, Leadership and Teamwork Skills

Effectively communicate/articulate the value and outcomes of business analytics to diverse audiences using written, oral, and analytical expression.

Effectively manage and lead teams engaged in analytics projects within the organization.

Analytics Strategy and Implications

Appraise analytical maturity of the organization in terms of its focus, culture, people, and technology.

Evaluate ethical, legal, and locational implications of data and decisions for stakeholders, internal and external to the organization.


MSBA course descriptions

BUAN600: MSBA Program Orientation (0 Credits)

A prerequisite for all other MSBA courses, this course introduces students to the MSBA curriculum and the approach to graduate academic engagement offered at the University of Redlands School of Business and its unique learning community.

BUAN610: Data Ethics for Business  (4 Credits)

This course evaluates the ethical, social, and legal ramifications of the choices we make at different stages of data analysis and information privacy, and the impact of those choices on managerial decision-making.

BUAN615: Competing with Analytics (4 Credits)

This course examines organizational contexts for business analytics. Focus is on creating competitive advantage across business functions such as marketing, operations, finance, human resources, R&D, and supply chain through strategic use of analytics. 

BUAN620: Data Science Foundations (4 Credits)

This course provides an in-depth understanding of data, data technologies, and techniques essential to effective analytics. The course also includes fundamental concepts and skills to effectively manage, clean, integrate, pre-process, and transform data for analytics using industry-standard tools such as Python or R.

BUAN630: Data Visualization & Storytelling (4 Credits)

This course evaluates the role of descriptive analytics, both statistical measures and visualization, in delivering organizational value to decision-making contexts. Coursework includes use of spatial-temporal data for “storytelling” and the effective communication of results to organizational decision-makers.

BUAN631: Data-Driven Decision-Making (4 Credits)

This course focuses on descriptive and predictive analytics for decision-making from a variety of business disciplinary perspectives. Important elements include identification of data-driven decision-making contexts in business, ascertaining data needs, analyzing data, interpreting and communicating results, and ultimately the value proposition of analytics.

BUAN640: Data Mining for Predictive Analytics (4 Credits)

This course provides an overview of data mining concepts, process, and popular methods in the context of business. Supervised and unsupervised methods are covered using large, real-life business datasets, with statistical modeling and machine learning support provided by programming. Spatial data mining, privacy issues, and pitfalls of data mining are discussed.

BUAN651: Prescriptive Analytics for Managerial Decision-Making (4 Credits)

This course provides students with an understanding of the role prescriptive analytics plays in organizational decision-making. Topics include quantitative methods such as optimization, simulation, forecasting, supply chain management, and project management for value creation in business functions.

One Elective Course (4 credits):

Students choose one of the following courses below to complete the elective course requirement.

    • BUAD 658: Accounting  and Finance for Managers (4 credits)
      This course focuses on the role of accounting and finance in managerial decision-making, including how managers access capital, invest in resources, budget operations, and report economic events.
    • BUAN 691 Introduction to Location Analytics and Marketing (4 credits)
      Students are introduced to the fundamentals of location analytics, including location value and spatial maturity and growth across business functions. Moving from fundamentals, the course focuses on the domain of marketing with focus on marketing applications of GIS and location analytics to enhance customer value by understanding, examining, and predicting the needs and preferences of the modern customer. Topics include environmental scanning, market segmentation, target marketing and promotions, and development of an integrated marketing plan using GIS as an analytic tool. This course may be substituted with GISB 691: Introduction to Location Analytics and Marketing.
    • BUAN 694 Location Analytics and Decision-Making (4 credits)
      This course focuses on decision-making spanning various stages of the location value chain in businesses employing GIS and location analytics. Emphasis is on illustrations of the process by which GIS and location analytics projects and business applications are planned, developed, and implemented. Topics include location analytics and spatial enablement in the enterprise, spatial decision support, location analytics to examine big data, social media, internet of things, mobile technologies and their spatial components, and costs, benefits, risks, and ethical implications of spatial projects and applications. This course may be substituted with GISB 694: Location Analytics and Decision-Making.
    • BUAN 660: Managerial Finance (4 credits)
      This course provides an overview of financial management tools used in analyzing and developing strategies for making business decisions. Topics include time value of money, bond and stock valuation, risk and return, capital budgeting, capital structure and dividend policy, working capital management, options and their applications in corporate finance. This course may be substituted with BUAD 660: Managerial Finance.
    • BUAN 683 Marketing Analytics (4 credits)
      Examination of the strategic planning process, with emphasis on resource allocation decision driven by marketing analytics. Focus on the use of quantitative and data analysis tools to define optimal marketing mix, perform effective analysis of customers and digital marketing campaigns, as well as integrate spatial thinking in decision making. This course may be substituted with MGMT 683: Marketing Analytics.
    • INTB 655: Global Environment for Business (4 credits) 
      This course explores the theoretical and practical concepts of geopolitical and economic relations to evaluate the effects of globalization on business. Focus is on evaluating and formulating strategic responses to diverse political, economic, and social factors regarding the risks they present for international trade and investment, resource allocation decisions, and organizational structures. This course may be substituted with INTB 670: International Area Studies.
    • MGMT 631: Management and Organizational Behavior (4 credits)
      This course focuses on key business areas such as managing individual performance, team and intergroup dynamics, leadership, human resource management, organizational design, decision making and management of change.
    • MGMT 680: Marketing Management (4 credits) 
      This course explores the crucial aspects of marketing with emphasis on the customer and the marketing mix, and includes development of analytical and critical thinking skills through case study, and the design and assessment of a basic marketing plan.

BUAN695: Analytics Capstone (4 Credits)

This course is the culmination of the MSBA program and includes an applied analytics project. Using knowledge gained throughout the program, students work on a real-world project that requires strategic deployment of analytics. Emphasis rests on improving decision-making and communicating the value generated by analytics.


Business & data analyst career forecast

According to the Bureau of Labor Statistics (BLS), employment of computer and information research scientists, including data analysts, is projected to grow 14 percent from 2018 to 2028, faster than the average for all occupations. Computer scientists are likely to enjoy excellent job prospects, because many companies report difficulties finding these highly skilled workers. Many companies are still trying to staff with a talent shortage in full force.

Business and data analysts are desired in almost every company or organization across every industry and can hold valuable jobs in finance, operations, marketing, healthcare, human resources, technology and other key business areas.

One of most read articles of all times in the Harvard Business Review is about Data Scientists: Data Scientist: the sexiest job of the 21st century by Thomas H. Davenport and D.J. Patil.

According to a report by PWC, data scientists, data engineers and business analysts are among the most sought-after positions in America. Yet, many existing and emerging workers don’t have the full skillset employers need.

According to a report released in February 2020 by Valuates, the global big data and business analytics market size was valued at $171.39 billion in 2018 and is projected to reach $512.04 billion by 2026, growing at a rate of 14.8 percent between 2019 and 2026.

According to a global research paper released in June 2020 by technavio, the global analytics market is expected to grow by $109.7 billion during 2020-2022 alone.

Business and data analysts are one of the top fastest-growing career fields with pay higher than other career fields, according to LinkedIn and

To review career and salary potential, click here.