The Master of Science in Business Analytics presents 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.

TOTAL UNITS -- 39

FOUNDATION COURSE -- 3 UNITS

MATH 240
Data Analysis for Managers

CORE COURSES -- 15 UNITS

MSBA 300
Foundations of Business Analytics
MSBA 301
Enterprise Performance Management & Metrics
MSBA 304
Managing Relational Structures
MSBA 305
Business Intelligence & Decision Support
MSBA 320
Advanced Statistical Analysis with R & Python

REQUIRED COURSES -- 15 UNITS

MSBA 321
Big Data Ecosystems
MSBA 324
Web & Social Network Analytics
MSBA 326
Predictive Analytics & Machine Learning
MSBA 327
Text Analytics
MSBA 395
Business Analytics Capstone Project

ELECTIVE COURSES -- 6 UNITS

MSBA 307
Analytics, Intelligence, Security, & Privacy
MSBA 322
Master Data Management
MSBA 328
Data Visualization & Communications through Storytelling

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LEARNING OUTCOMES

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 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.

BUSINESS ANALYTICS DEPARTMENT

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