Business Analytics Specialization

(Formerly Data, Models & Decisions)

The business analytics specialization deals with the use of data and mathematical and statistical models as a means for aiding the decision process in all of the functional areas of business.  The use of data and models has become very important in business because of the volume of data available as a result of the internet and the increasing number and sophistication of electronic touch points among people and business and government entities. The use of computer and information technology plays an important part in this specialization. 

A specialization in business analytics enables the student to understand and use different mathematical and statistical models to apply to their own area of interest.  As examples:
  1. A financial analyst may want to predict returns on a stock or index based on historical data.
  2. A production engineer may want to predict the time it takes to complete a given task in terms of characteristics of that task.
  3. A media buyer may want to measure the impact of advertising and other variables on sales.
A specialization in business analytics allows students to choose from a menu consisting of a wide variety of relevant courses in statistics, operations, information technology, and marketing, according to their area of interest and career path.  The skills learned in these specializations would help them be more effective in their careers as Financial Analysts, Consultants, and Marketing Research experts.

Academic Advisor: Professor Norman White, 212-998-0842

Course List

Take 9 credits from the following list: 

Course Number Course Title
ACCT-GB.3328 Financial Statement Analytics Using Python
ECON-GB.3351 Econometrics I
FINC-GB 3324  Digital Currency, Blockchains & the Future of the Financial Services Industry
INTA-GB.2312 FinTech Risk Management 
MKTG-GB.2327 Research for Customer Insights
MKTG-GB.2344 Data Driven Decision Making: Managerial
MKTG-GB.2354 Data Driven Decision Making: Technical
MKTG-GB.2355 Retail Strategy & Analytics
OPMG-GB 2308 Retail Operations & Supply Chain Management*
OPMG-GB.2310 Managing for Quality
OPMG-GB.2330 Retail Operations*
OPMG-GB.2350 Decision Models and Analytics
OPMG-GB.2351 Decision Making Under Uncertainty
OPMG-GB 2354 Decision Analytics for Sports
OPMG-GB.3330 Revenue Management and Pricing
STAT-GB.2301 Regression and Multivariate Data Analysis
STAT-GB.2302 Forecasting Time Series Data
STAT-GB.2308 Applied Stochastic Processes for Financial Models
STAT-GB.2309 Mathematics of Investment
STAT-GB.3127 Statistical Aspects of Market Risk
STAT-GB.3301 Introduction to the Theory of Probability
STAT-GB.3302 Statistical Inference and Regression Analysis
STAT-GB.3306 Time Series Analysis
STAT-GB.3310 Applications of Statistical Methods to Business, Politics and Policy
STAT-GB.3321 Introduction to Stochastic Processes
TECH-GB.2114 Introduction to Cybersecurity and Privacy Management
TECH-GB.2134 R Programming for Data
TECH-GB.2135  Programming in Python
TECH-GB.2318 Digital Strategy
TECH-GB.2335 Programming in Python and Fundamentals of Software Development
TECH-GB 2336 Data Science for Business Analytics - Technical
TECH-GB.2346 Dealing with Data
TECH-GB.2350 Robo Advisors and Systematic Trading
TECH-GB 3106 Data Visualization
TECH-GB.3162 Emerging Technology and Business Innovation
TECH-GB.3306 Data Visualization
TECH-GB.3310 Social Media and Digital Marketing Analytics
TECH-GB.3322 Design and Development of Web and Mobile Applications
TECH-GB.3332 Introduction to AI & Its Applications in Business
TECH-GB.3333 Practical Big Data 
TECH-GB.3336 Data Mining for Business Analytics - Managerial
TECH-GB.3339 Being Digital: Search, Social Media and Crowdsourcing
TECH-GB.3347 Fundamentals of Digital Marketing Technologies
TECH-GB.3350 Financial Information Systems
TECH-GB.3351  Risk Management in IT
TECH-GB.3359 Practical Data Science
TECH-GB.3362 Emerging Technology and Business Innovation

*Students may count OPMG-GB 2308 Retail Operations & Supply Chain Management or OPMG-GB 2330 Retail Operations, not both. 

For course descriptions, please see the Office of Records & Registration website.