Business Analytics, MS (Worldwide)

Program Information

The Master of Science in Business Analytics (MSBA) degree program is to present students with an understanding of the many possibilities for applying data analytics to business problems. Data analytics, and the implications of this strategic discipline, give practitioners new opportunities for discovering insights that can support the strategic goals and decision making of the organization. The discipline has grown so fast that it is impossible to address all of its elements, so this degree should be viewed as a “toolkit” of statistical and analytic theory, processes, tools, and techniques, which can be integrated into the business depending on the discipline and needed outcomes.

The MSBA is relevant to multiple audiences, including: the business manager charged with using data analytics to derive value from data and/or leveraging analytics teams to get that value; the subject matter expert (SME) in a business discipline charged with using analytics on the job; the budding business analytics data scientist requiring understanding of a myriad of data analytics tools from which to draw, and the IT professional responsible for supporting the analytics infrastructure and addressing issues of data security, privacy and ethics. This program is a STEM-designated degree program.

Student Learning Outcomes

Graduates of the Master of Science in Business Analytics degree program will have the knowledge and skills to:

Explain the differences between structured and unstructured data, aligning each with appropriate business applications.
Articulate and align with corporate performance, the complexities of data management, including organizational structures, data policy, data governance, data ownership, and data strategies.
Explain and give examples of the three analytic disciplines of descriptive, predictive, and prescriptive (optimization).
Identify the different kinds of tools used in optimization and simulation and explain their appropriate usage in the work environment.
Identify and explain the steps of the CRISP-DM process model.
Anticipate challenges to data security, privacy and ethics, recommending reasonable solutions to issues when they occur.
Recognize the challenges of Big Data and describe the use of supporting technologies.
Use visual outcomes of analytics to communicate effective messages to members of the business community.
Describe the different approaches to machine learning, demonstrating application of the most common algorithms.
Explain Natural Language Processing, identifying potential uses and challenges.
Interpret and analyze individual business problems, selecting the best analytic approach and appropriate tools for extracting value from the data.
Explain the differences between the R and Python programming languages and demonstrate proficiency in each.
Promote data quality by effectively acquiring, cleansing, and organizing data for analysis.

Student Manual

Students must abide by the polices stated in the MS in Business Analytics Student Manual .

Requirements for the Master of Science in Business Analytics

The Master of Science in Business Analytics requires completion of 36 units in the graduate program and a 3-unit graduate statistics course. Students must earn a grade of “C-” or better in each course and cumulative grade-point average of 3.00 or better. Study abroad program students who are unable to obtain a visa to study in the U.S. will be awarded the Global Business Analytics Professional Certificate (Worldwide) upon completion of the online portion of the program.

Mathematics Proficiency Requirement

BUS 240 Data Analysis for Managers (Waived with documentation of student’s having completed equivalent course covering statistics and regression analysis with grade of “B” or better.)

Business Analytics Courses - 36 units

MSBA 300 Foundations of Business Analytics 3 unit(s) *
MSBA 301 Enterprise Performance Management and Metrics 3 unit(s) *
ITM 304 Managing Data Structures 3 unit(s) *
MSBA 305 Business Intelligence 3 unit(s) *
MSBA 320A Advanced Statistical Analysis with R 3 unit(s) *
MSBA 320B Advanced Statistical Analysis with Python 3 unit(s) *
MSBA 321 Big Data Ecosystems 3 unit(s)
MSBA 324 Web and Social Network Analytics 3 unit(s)
MSBA 326 Machine Learning for Predictive Analytics 3 unit(s)
MSBA 327 Natural Language Processing 3 unit(s)
MSBA 329 Prescriptive Analytics and Optimization 3 unit(s)
MSBA 395W Business Analytics Capstone 3 unit(s)
*These courses will be completed online via upGrad’s learning management system.

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