Master of Science in Business Analytics
The Master of Science in Business Analytics (MSBA) program is a full-time degree program that equips students with the business skills and practical experience to ready themselves for careers in data science and analytics. Program requirements are completed with classes that will also include students from the MBA and other M.S. programs. The MSBA program is taught by the same faculty as the MBA program, and has the same Association to Advance Collegiate Schools of Business International (AACSB) accreditation. A new cohort is admitted once a year.
Admissions intake once a year (Fall Quarter, September start)
Deferments are generally not permitted
Two years of professional work experience recommended, but not required
An interview is required
Applicants also must have successfully completed the following areas prior to enrollment:
One (1) course in college level calculus
One (1) course in college level statistics
Applicants must complete and submit the following items before the Admissions Committee will render an admissions decision:
Submit an online application form and $158 application fee paid by credit card
Academic Records and Transcripts*
Official GMAT or GRE exam results
Official TOEFL exam results. If your first language is not English, submit your official TOEFL (preferred) or IELTS test score. TOEFL is waived(if the Verbal section of the GMAT or GRE is above the 50% mark.
Two (2) Letters of Recommendation
Online application fees must be paid by credit card and submitted electronically.
Applicants must have their official GMAT or GRE score reports sent directly to the Graduate Business Admissions Committee. Applicants whose first language is not English must either achieve a minimum score of 100 on the TOEFL (internet-based test) or a 7 on the IELTS.
Foreign-born admitted students requesting student visas must submit a current financial statement (no more than 90 days old) showing adequate funds for tuition, fees, and living expenses for the first year of study, and they must be enrolled in at least 8 units each quarter. Santa Clara University is authorized under federal law to enroll nonimmigrant students.
Applicants are responsible for the appropriate submission of all application materials, including:
Application form, resume, fee, and essay responses submitted online
Recommendation letters and transcripts
GMAT/GRE and TOEFL/IELTS/PTE scores sent directly from the test center to the MSBA Admissions Committee
The MSBA Admissions Committee will not review applications until all materials have been received.
* Undergraduate degrees conferred outside of the US are required to be evaluated by WES using their ICAP, course-by-course evaluation.
Please refer to https://www.scu.edu/business/ms-business-analytics/ for additional information.
The MSBA program requires 42 units to complete the degree.
Below are the required courses and their corresponding units:
FNCE 2502 - Math for Finance and Analytics w/ R (4 units)
ECON 2509 - Econometrics w/ R (4 units)
MSIS 2507 - Data Analytics - Python (4 units)
MKTG 2505 - Marketing Analytics (4 units)
MSIS 2503 - Database Management Systems - Fundamentals of SQL (2 units)
MSIS 2508 - Data Science & Machine Learning (4 units)
MSIS 2510 - Prescriptive Analytics (4 units)
Up to 6 units of experiential learning
Students can then choose additional elective units to complete their degree. A sample of the electives offered are as follows:
MSIS 2513 - Database Management Systems - Design, Development & Administration (2 units)
FNCE 2524 - Time-Series Analysis (2 units) - additional prerequisite required.
FNCE 2525 - Analytics of Finance (2 units) - additional prerequisite required.
FNCE 2526 - FinTech (4 units) - additional prerequisite required.
MSIS 2527 - Big Data Modeling and Analytics (4 units)
MSIS 2528 - Applied The Business of Cloud Computing (2 units)
MSIS 2529 - Dashboards (2 units)
MSIS 2536 - Deep Learning (2 units)
MSIS 2537 - Reinforcement Learning (2 units)
MSIS 2538 - Cloud Computing Architectures (4 units)
MSIS 2539 - Data Visualization (2 units)
Additional electives may be added and will be numbers 25xx.
Note: Please refer to Chapter 12 for all course descriptions.
Course Waiver Policy
Due to the full-time nature of the MSBA program, a student requiring a leave of absence will be required to withdraw from the program. Alternatives to continuing his/her education should be discussed with the MS Program Director.
Students who want to withdraw from the program and the university must notify the Graduate Business Programs Office of their intent in writing. Some portion of the tuition may be refunded and will be determined at time of withdrawal notification. Withdrawal from the university is not complete until the student clears obligations with the Bursar's Office.
Transferring into Another Graduate Business Program
Transferring into another graduate business program is possible if the student is in good academic standing and has a minimum GPA of 3.0. A transfer will be granted only once, by application, and is at the discretion of the director of admissions and the senior assistant dean.
Applications can be submitted between September 15th and March 15th of each academic year. Students wishing to apply for a transfer to another graduate business program will need to complete the following:
M.S. transfer application
A brief personal statement (1 page) advocating transfer
A recommendation from a SCU faculty member attesting to performance and supporting the transfer
The Faculty Director(s) and Senior Assistant Dean will review the application, personal statement, and recommendation in concert with the student's GRE/GMAT score and academic performance in the current M.S. program before making a decision on the request. A transfer back to the MSBA is not possible once the student is approved to transfer to another graduate business program.
For information regarding entrance into the MBA program after completion of the MSBA program, contact the Graduate Business Admissions Office, 116 Lucas Hall.
To qualify for the MSBA degree, a student must maintain an overall grade point average (GPA) of at least 3.0 in all work taken in the Leavey School of Business. A grade of C- is considered a minimum passing grade in each course. A grade of F is considered a failing grade, and the units will not be counted toward graduation requirements.
Students who receive an F in a required course are eligible for immediate dismissal based on the availability of the course and its requirement as a prerequisite for other courses.
If a student has a cumulative GPA below a 3.0, they will be placed on academic probation. A student then has one quarter to raise the GPA to a cumulative 3.0 or they will be dismissed from the program. Students failing required classes may be dismissed immediately if it is mathematically impossible to return to good standing and remain on track to graduate with their class.
The administration will contact faculty midway through the term to acquire a status update on academic performance to ensure students are aware of academic resources and tutoring in an attempt to resolve matters before they affect GPA.
If a student has a cumulative GPA below a 3.0 at the end of their final quarter and all course requirements have been satisfied, no degree will be awarded until the cumulative GPA is a 3.0 or better through completion of additional graduate course work in the Leavey School of Business.
Students enrolled in the MSBA program are required to follow the same policies and procedures as students in the evening MBA program. Each student is personally responsible for knowing all of the academic regulations of the graduate business school. This includes, but is not limited to: grading, honor code, leave of absence, withdrawal, and concurrent enrollment policies. Please refer to the Academic Information section, Chapter 4, for additional information.
MSBA Core Course Descriptions
MKTG 2505. Marketing Analytics
Prepares managers to identify the competitive advantages that come from leveraged analytics, apply and implement tools, evaluate advantages and limitations, ask relevant business questions and interpret and communicate the output from tools and models to achieve profitable business decisions. Prerequisite: MKTG 2500 & MSIS 2506. (4 units)
MSIS 2503. Database Management Systems - Fund of SQL
This course presents technical and managerial approaches to the analysis, design, and management of business data, databases, and database management systems. The topics include structured and unstructured data management, a comparison of relational and object-oriented databases, relational database conceptual and logical design, and database implementation and administration. (2 units)
MSIS 2507. Data Analytics - Python
Data analytics involves the application of scientific methodologies to extract, understand, and make predictions based on data sets from a broad range of sources. Data analytics requires knowledge and skills from three areas: (i) programming, (ii) math/statistics, and (iii) domain specific expertise. (4 units)
MSIS 2508. Data Science and Machine Learning
This course introduces participants to quantitative techniques and algorithms that are based on big and small data (numerical and textual). We also analyze theoretical models of big systems for prediction and optimization that are currently being used widely in business. It introduces topics that are often qualitative but that are now amenable to quantitative treatment. The course will prepare participants for more rigorous analysis of large data sets as well as introduce machine learning models and data analytics for business intelligence. (4 units)
ECON 2509. Econometrics w/ R
Covers the basic conceptual foundations and tools of econometrics and apply them to case studies with real-world data. The key statistical technique used in this course is multiple linear regression and R programming. (4 units)
FNCE 2502. Math for Finance and Analytics w/ R
To provide a comprehensive background in the mathematical topics required for learning Quantitative Finance (QF) and Business Analytics and Data Science (BADS). The mathematical topics covered include Calculus, Linear Algebra and Probability Theory. Applications of these topics in a variety of business contexts will be included. (4 units)
MSBA Elective Course Descriptions:
FNCE 2523. Introduction to FinTech
FinTech has rapidly become a prevalent part of our vernacular, and an understanding of the evolution of traditional finance methods is an important part of a Finance majors arsenal. This course covers the evolution of traditional finance methods -- namely, the disruptions and innovations that have transformed: (i) how we access capital; (ii) how we allocate or invest capital; (iii) how we settle or transfer capital; and (iv) how we monitor and maintain the integrity of financial institutions and transactions. (2 units)
FNCE 2524. Introduction to Time Series
This course is designed to provide comprehensive introduction to forecasting methods used in Time Series Analysis. The class covers a range of topics in time series forecasting. The class will provide you with a language to describe time series data and ultimately cover modeling techniques such as ARIMA, SARIMA, and GARCH to produce forecasts. (2 units)
FNCE 2525. Analytics for Finance
This course covers key issues in panel data analysis, with an emphasis on their applications in empirical research, especially empirical corporate finance. The course aims to introduce various econometric methods for analyzing panel data and develop core techniques to identify causal relations in the data. We will begin with the standar linear regressions, and extend to pooled, fixed effect and random effect regression models, instrumental variables, differences in differences, selection models, and regression discontinuity. Students will be exposed to a broad range of applications in finance through reading academic papers and conducting their own empirical analysis. (2 units)
MSIS 2527. Big Data Modeling and Analytics
This course is about Big Data and its role in carrying out modern business intelligence or actionable insight to address new business needs. This course is a leb led and open source software rooted course. Students will learn the fundamentals of Hadoop framework, NoSQL databases and R Language. The class will focus on storage, process analysis and aspects of Big Data. Students will have access to a MapR Hadoop Image. The image is enhanced by Instructor to include MOngoDB and R. (4 units)
MSIS 2529. Dashboards
This course enables you to transform data into persuasive dashboards that effectively inform and guide management actions. Dashboards are persuasive if they motivate actions in an intended audience. Dashboards are effective if they offer comprehensive and reliable information. This course introduces and discusses the fundamental design principles and technology of dashboards and allows you to design, implement, and critique dashboards. (2 units)
MSIS 2539. Data Visualization
This course enables you to explore data, identify insights and develop evidence-based arguments using data visualization techniques. Completing this course equips you with a moderate level of data literacy, the ability to interpret, construct and convey arguments through the functional and truthful visual presentation of data. You will wrangle data, customize data visualization technologies and programmatically develop data visualizations. (2 units)
OMIS 2596. MSBA Internship
Enriches the academic experience of MSBA students through a structured experiential-learning program. Designed as a partnership between the Leavey School of Business, partner employers, and the MSBA student, the experiences gained through an internship complements classroom learning, and provides an extension of the classroom experience, integrating theory and practice. Course cannot be repeated for credit. Course only offered in Summer quarter. (1 unit)
OMIS 2597. MSBA Internship
A continuation of the internship curriculum started in OMIS 2596. Course cannot be repeated for credit. Course only offered in Fall quarter. Prerequisite: OMIS 2596 and MSBA student. (1 unit)