Master of Science in Business Analytics (MSBA)
A comprehensive graduate program providing the knowledge and skills needed to apply data analytics to real-world business issues.
The purpose of 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. Students completing the MSBA will have earned 39 units including three units of graduate statistics.
Graduates of the Master of Science in Business Analytics will be able 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 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 the 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, cleaning, and organizing data for analysis.
Golden Gate University's Business Analytics programs are overseen by an advisory board comprising business and academic leaders in the field.
- Rich Clayton, VP Business Analytics Product Group, Oracle
- June Dershewitz, Head, Data Analytics and Governance, Twitch
- Tracey Edwards, Managing Principal Global Shared Services & CKO (ret), Deloitte
- Michael Evans, National Managing Director, Newport Board Group
- Richard Harris, VP Digital Product Engineering, GE Aviation
- Dr. Zoher Karu, Formerly VP, Chief Data Officer, eBay Inc.
- Stuart McGuigan, Chief Information Officer, Johnson & Johnson
- David McGuire, Sr. Director, Global Media & Marketing Ops, SunPower, Corp
Admission to the program is selective and limited. To receive full consideration, applicants must submit all required materials by the preferred application deadline. Completed applications will be reviewed by the committee on a weekly basis and qualified applicants will be notified of their admission on an ongoing basis until the incoming class is completed.
Golden Gate University seeks a well-rounded group of students from diverse educational and professional backgrounds. Ideal candidates will have a balance of both quantitative skills and business skills. Students will be selected based on academic transcripts, a statement of purpose, and a resume.
Graduate degree programs require proficiency in writing to ensure that students are successful in their course of study.
Students will need to have an understanding of United States business practices to be successful in our graduate programs.
Students admitted to this program are expected to possess a level of mathematical skill at least equivalent to MATH 20, Intermediate Algebra.
79 TOEFL or 6.5 IELTS or 57 PTE is the minimum exam score.
TOTAL UNITS -- 39
FOUNDATION COURSE -- 3 UNITS
- MATH 240 Data Analysis for Managers
CORE COURSES -- 18 UNITS
- MSBA 300 Foundations of Business Analytics
- MSBA 301 Performance Management & Metrics
- MSBA 304 Database Theory & Data Management Tools
- MSBA 305 Business Intelligence & Decision Support
- MSBA 307 Analytics, Intelligence, Security, & Privacy
- MSBA 320 Tools for Business Analytics
ADVANCED COURSES -- 18 UNITS
- MSBA 321 Managing Big Data Frameworks
- MSBA 324 Web & Social Analytics
- MSBA 326 Predictive Analytics & Machine Learning
- MSBA 327 Text Analytics
- MSBA 328 Data Visualization & Communications through Storytelling
- MSBA 395 Business Analytics Capstone Project
International Student Welcome Scholarship
Golden Gate University welcomes international students from all over the world. We are excited to introduce a one-time scholarship for all international students who enroll in our Graduate Degree Program and meet the requirements. You may receive a scholarship in the amount of up to USD $2,000 off tuition.
Cost & Fees
$3,045 per 3-unit course
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Last updated April 30, 2018