Curriculum

Degree Requirements

To be eligible for the M.S. in Business Analytics you must have been Advanced to Candidacy (see Graduate Degree Information chapter of the catalog) and have completed 45-53 quarter units meeting the following criteria:

  • All have a course grade of "C" or better.
  • Have a combined 3.0 grade point average (minimum) in all units taken to satisfy the requirements of the student's degree program.
  • Have no more than 20 units for extension and/or transfer credit (any extension and/or transfer credit must be approved by the Program Director) and/or coursework taken in "Unclassified Postbaccalaureate" status.
  • All units earned within the five years immediately preceding the completion of the requirements for the degree.
  • Have completed a satisfactory program of study, defined below.

Fundamental Courses (0-8 units)

Fundamental coursework must be completed before enrolling in any M.S. in Business Analytics. required course. Fundamental courses may be waived if a student completed equivalent coursework for one or both fundamental courses, or completed the undergraduate version of these fundamental courses, i.e., ITM 3060 and MGMT 3100, within the last five years with a grade of “C” or higher. Fundamental coursework can be also waived by passing an exam. Exams are offered once per quarter. There is a fee of $25 for each exam. Please see the M.B.A. website or contact the CBE Graduate Programs Office (VBT 430, phone 510-885-2419) for dates and registration information.

  • ITM 6015 Information Systems Development and Management (4)
    • Development of business information technology strategies and solutions for enterprise and global information management systems. Topics include the structure, analysis, design, and implementation of information technology systems. A-F grading only.
  • MGMT 6015 Data Analysis and Decision Modeling for Managers (4)
    • Quantitative modeling and data analysis as they are applied for making managerial decisions in organizations. Topics include regression, correlation, forecasting models, optimization, decision analysis, project management, and simulation. Emphasis on usage of spreadsheet modeling and appropriate software technology. A-F grading only.

Required Courses (24 units)

Required courses will be taught with modern data analytics programming languages and tools, e.g., SQL, Hadoop, SAS, R, Python, Excel-based add-ins, etc.

ITM 6271 Database Management and Applications (4)

    • Data modeling, database design and implementation, database administration, and database applications. Topics include: database design, incorporating business rules into entity-relationship (ER) models, transformation of an ER model into a relational database design, normalization of database tables, SQL data definition language and data manipulation language, views, triggers, data dictionary, and the Internet database environment.
ITM 6273 Big Data Technologies and Applications (4)
    • Computerized support for knowledge management.  Topics include: the concepts and tools of knowledge management, data visualization, data management, text and Web mining concepts and applications, and big data technologies and tools such as Hadoop. Prerequisites: All fundamental coursework: ITM 6015MGMT 6015. A-F grading only.

MGMT 6160 Data Analytics (4)

    • Examining raw data to draw conclusions about information. Topics include a broad set of analytical methodologies, with a focus on multiple regression methods and time-series applications in big data analytics. Prerequisites: MGMT 6015  or consent of instructor. A-F grading only.

ITM 6280 Data Warehousing (4)

    • Data warehousing concepts, design, implementation, and software tools. Topics include data warehouse architecture, dimensional model design, physical database design, data integration and visualization, and data warehouse administration. Prerequisites:ITM 6271 or instructor consent. A-F grading only.

ITM 6285 Data Mining (4)

    • Big data and data mining software applications; introduction to and study of the concepts and technologies of data mining. Topics include data preparation and classification, clustering, prediction, scalability, and data visualization, evaluation and ethical issues in data mining. Prerequisites: ITM 6271 or instructor consent. A-F grading only.
  • MGMT 6165 Prescriptive Analytics (4)
    • Determining the best solution among various choices, suggesting decision options, and illustrating the implications of each option. Topics include: optimization methods, decision making under uncertainty, queuing models, simulation, and application-based software. Prerequisites: MGMT 6015 or consent of instructor. A-F grading only.

Elective Courses  (20 units)

Select five courses from the following:

  • ITM 6130 Enterprise Management Systems (4)
    • Design, selection and implementation of enterprise resource management (ERM) and enterprise resource planning (ERP) systems. Emphasis on integration and automation of business functions. Development of practical skills and utilization of enterprise resource planning software.
  • STAT 6250 SAS Programming (4)
    • Professional SAS programming techniques. Data management and processing. Data integrity. Graphical presentation of data. Data reporting techniques. Topics in applied statistics and biostatistics. Introduction to SAS data step, SAS Macros, SAS Reports, SAS SQL, and other relevant programming topics. Report Writing. Prerequisites: Current enrollment or completion of a graduate level course in statistics.
  • FIN 6310 Seminar in Security Analysis and Portfolio Management (4)
    • Theory and practice of security investment. Investment environment and instruments, capital asset pricing theory, technical and fundamental analysis of common stock portfolio analysis, bond analysis and management, mutual funds and investment companies, and financial derivatives.
  • MKTG 6401 Marketing Research (4)
    • Knowledge and training in process and techniques of acquiring, analyzing, interpreting and reporting information for decision-making. Topics include data collection instruments, sampling plan, statistical analysis and reporting of results. Hands-on learning is emphasized through assignments and/or project.
  • MGMT 6155 Applied Project Management (4)
    • Analysis of modern methods and tools of project management. Topics include project definition, time and resource scheduling, budgeting, risk management, and performance measurement. Emphasis on developing practical skills in managing projects through case studies and utilization of project management software. A-F grading only.
  • ECON 6511 Advanced Applied Econometrics (4)
    • Applied Statistical Models, including multiple regression, simultaneous equation models, time series models, and logistic regression/binary choice models. Cross-listed STAT 6511A-F grading only.
  • MGMT 6622 Human Resources Analytics (4)
    • This course investigates the critical role of Human Resources (HR) Management in identifying, collecting and analyzing the human capital metrics needed for strategic development of organizational effectiveness. Topics covered include HR measurement; HR data analyses and research design; as well as using data in strategic decision-making for key HR functions such as staffing and selection, employee retention, performance management, and employee health and wellness.  
  • STAT 6620 Statistical Learning with R (4 units, effective Fall 2016)

Potentially, one graduate course may be approved by the program advisor (graduate coordinator)

Capstone Experience (1 units)