MS in Business Analytics

The Master of Science in Business Analytics (MSBA) prepares students for positions across fields of business. The program begins by providing a foundation in data analysis and programming skills, and then moves into preparation in statistics and machine learning. The program then concludes with a focus on data analysis challenges businesses face across disciplines such as marketing, operations/supply chain, accounting/finance, human resources, and health sector analytics.

Learning Outcomes

The MS in Business Analytics will seek to develop graduates who will:

• Be able to think critically about and frame data problems in a variety of business contexts and apply appropriate analytical methods to find solutions that achieve stated objectives.
• Consider opportunities, needs, and constraints of data analytics within the business functions and the strategic importance of decisions made using data.
• Demonstrate critical-thinking skills, connecting quantitative and qualitative tools, concepts, and context to effectively solve problems and make decisions.
• Demonstrate proficiency with a variety of data-analytic tools.
• Demonstrate an understanding of how advanced data analytics, data mining, and artificial intelligence (AI) can be employed to create a business value and address business problems.
• Communicate technical information to both technical and non-technical audiences in speech, in writing, and graphically.
• Demonstrate interpersonal, team, collaborative, and leadership skills.
• Demonstrate ethical reasoning skills and understand professional responsibilities.
• Demonstrate proficiency in a concentration area, if chosen.

Curriculum

The MS in Business Analytics program is a full-time program which allows students to complete the program in 36 units. Depending on each student’s academic plan and career objectives, the program starts in the fall and may be paced to be completed in 12 months over three consecutive terms (fall, spring, summer), or in 16 months over three terms with an interspersed summer, which may be used to complete a summer internship. Students may also elect to complete a concentration as part of their program. All students begin the program cohorted with a common set of core courses. Given the intensity of the program, all students must receive the permission of the Faculty Director to take any additional courses outside of the program. Any questions related to curriculum sequence can be discussed with the student’s academic advisor.

Required Prerequisites

All students enrolling in the MSBA program must demonstrate introductory knowledge of Python programming and fundamentals of statistics and data analysis by either successfully completing a required noncredit bootcamp, prior coursework as determined through the admissions process, and/or other approved coursework prior to matriculation.

Required Core (24–27 units)

• QST BA 600 Introduction to Programming with Python (0 units)
• QST BA 602 Fundamentals of Data Analysis and Statistics (0 units)
• QST ES 620 Career Foundations (0 units)
• QST ES 621 Career Workshop—Fall (0 units)
• QST ES 622 Career Workshop—Spring (0 units)
• QST BA 690 Launch (0 units)
• QST BA 777 Business Analytics Toolbox (3 units)
• QST BA 780 Introduction to Data Analytics (3 units)
• QST BA 805 Business Fundamentals for Analytics (1.5 units)
• QST BA 808 GenAI for Business Analytics (1.5 units)
• QST BA 810 Supervised Machine Learning (3 units)
• QST BA 820 Unsupervised and Unstructured Machine Learning (3 units)
• QST BA 830 Business Experimentation and Causal Methods (3 units)
• QST BA 840 Data Ethics: Analytics in Social Context (3 units)
• QST BA 888 Capstone Project (3 units) Required only for students completing the program in a 12-month format.
• QST BA 889 Analytics Practicum (0 units)
• QST BA 891 Analytics Practicum II (0 units)
• QST ES 711 Teaming (1.5 units)
• QST ES 729 Storytelling with Data (1.5 units)

Electives (9–12 units)

Students completing the program in 12 months must choose 3 electives (9 units). Students completing the program in 16 months must choose 4 electives (12 units). Available and approved electives are subject to change.

• QST BA 815 Competing with Analytics (3 units)
• QST BA 843 or IS 843 Big Data Analytics for Business (3 units)
• QST MK 856 Consumer Insights (3 units)
• QST BA 860 Marketing Analytics (3 units)
• QST BA 865 Neural Networks in Business: From Foundations to Generative AI (3 units)
• QST BA 870 Financial Analytics (3 units)
• QST BA 875 Operations and Supply Chain Analytics (3 units)
• QST BA 878 Machine Learning and Data Infrastructure in Healthcare (3 units)
• QST BA 880 or QST MO 860 People Analytics (3 units)
• QST BA 881 Analytics for Customer Strategies (3 units)
• QST BA 882 Deploying Analytics Pipelines (3 units)
• QST BA 885 Advanced Analytics 2 (3 units)
• QST BA 888 Capstone Project (3 units) May be taken as an additional course with program approval only (and based on seat availability) in the 16-month format.
• QST HM 817 Advances in Digital Health (3 units)
• QST HM 848 Driving Health Sector Innovation (3 units)
• QST MK 852 Data-Driven Marketing Decisions (3 units)
• QST MK 856 Consumer Insights (3 units)
• QST MK 864 Pricing Strategy & Tactics (3 units)
• SPH BS 803 Statistical Programming for Biostatisticians (3 units)
• SPH BS 806 Multivariable Analysis for Biostatisticians (3 units)
• SPH PM 804 Digital Disruption in Health (2 units)
• SPH PM 827 Strategic Management of Healthcare Organizations (4 units)

Total units required to earn the MSBA degree is 36 units for all students.

Concentrations

Students may pursue an optional concentration as part of their program. To earn a concentration, students must complete at least three courses in the area of concentration. Students should consult with their academic advisor regarding whether a concentration will fit into their desired completion timeline and academic goals. Concentration requirements are listed below.

Data & Methods

• CDS DS 690 Directed Study (3 units)
• QST BA 843 or IS 843 Big Data Analytics for Business (3 units)
• QST BA 865 Neural Networks in Business: From Foundations to Generative AI (3 units)
• QST BA 882 Deploying Analytics Pipelines (3 units)
• QST BA 885 Advanced Analytics Topics II (3 units)

Healthcare Analytics

• QST BA 878 Machine Learning and Data Infrastructure in Healthcare (3 units)
• QST HM 817 Advances in Digital Health (3 units)
• QST HM 848 Driving Health Sector Innovation (3 units)
• SPH BS 803 Statistical Programming for Biostatisticians (2 units)
• SPH BS 806 Multivariable Analysis for Biostatisticians (3 units)
• SPH PM 804 Digital Disruption in Health (2 units)

Marketing Analytics

• QST BA 860 Marketing Analytics (3 units)
• QST MK 852 Data-Driven Marketing Decisions (3 units)
• QST MK 856 Consumer Insights (3 units)
• QST MK 864 Pricing Strategy & Tactics (3 units)

Satisfactory Academic Progress

The Specialty Master’s & PhD Center monitors students’ academic performance during and at the end of the fall and spring terms. A student must maintain a cumulative grade point average (CGPA) of at least 2.70 (on a 4.0 scale) to remain in good academic standing during their studies and to graduate. Coursework taken outside Questrom School of Business, which does not count toward the MS in Business Analytics degree, will not be calculated into a student’s CGPA.

Student academic progress will be assessed against this standard at the midpoint and end of each term by the MSBA Program Development Committee (PDC). The review may result in a warning, academic probation with explicit expectations for improvement, or discontinuation from the program. A student who fails to make sufficient progress has the right to appeal. The process for appeal is fully described in MSBA Student Handbook.

Degree Completion

To qualify for the MS in Business Analytics, students must:

• Successfully complete all required courses for a total of 35.5 units.
• Have a cumulative GPA of at least 2.70.

Have no “I” grades or no “MG” grades in courses counting toward the degree.