Business Analytics Joint Concentration

The Business Analytics joint concentration between the OID and STAT departments is designed to build deep competency in the skills needed to implement and oversee data-driven business decisions, including (i) collecting, managing and describing datasets, (ii) forming inferences and predictions from data and (iii) making optimal and robust decisions. Business analytics makes extensive use of statistical analysis and the applications of business analytics span all functional areas.

Business analytics has emerged in recent years as a powerful and required capability for firms in competitive markets. The quantity, quality and diversity of available data have never been greater, which has created new and significant opportunities for organizations to use data to improve their decisions with respect to both internal resources as well as external interactions with suppliers and customers.

Students choosing the Business Analytics concentration are ideally suited for the growing set of careers broadly defined under the header of “data science” with responsibilities for managing and analyzing data. In addition, the concentration provides an excellent complement to students who choose to focus on one of the functional areas of business (e.g., accounting, finance, marketing, operations).

Concentration Requirements

Beyond core course requirements in OID (OIDD 101) and STAT (STAT 101 and STAT 102), students must complete 4 credit units from the set of approved courses listed below. Furthermore, among the set of selected courses, there must be at least 1 CU that provides competency for each of the following three fundamental skills in business analytics:

  1. Data collection (c): methods for acquiring and manipulating data
  2. Advanced data analysis (a): working with data sets in a computing environment
  3. Optimization (o): computer-based prescriptive decision making

Some courses provide competency in more than one of the above skills. Some courses are approved electives that do not focus on the set of fundamental skills but are nevertheless relevant for the management and implementation of business analytics. The skills provided by each course are indicated below with a “c”, “a” or “o”.

Students may select at most 1 CU outside of Wharton. Courses below are 1 CU unless otherwise noted.

Approved Undergraduate Courses

ACCT270 (a, c): Predictive Analytics Using Financial Disclosures

BEPP280 (a): Applied Data Analysis and Causality for Business and Public Policy

CIS 399: The Science of Data Ethics

+CIS419/519(a): Introduction to Machine Learning

CIS450 (c): Database and Information Systems

+CIS520 (a): Machine Learning

CIS545 (a, c): Big Data Analytics

ESE301: Engineering Probability

ESE305 (a): Foundations of Data Science

ESE504 (o): Introduction to Optimization Theory

FNCE237 (a,c): Data Science for Finance

HCMG 357 (a,c): Health Care Data and Analytics

LGST242: Big Data, Big Responsibilities: The Law and Ethics of Business Analytics

MGMT293 (a, c): People Analytics

MKTG212 (a): Data and Analysis for Marketing Decisions

MKTG271 (a): Models for Marketing Strategy

MKTG309 (a, c): Experiments for Business Decision Making

MKTG352 (a, c): Marketing Analytics

MKTG476 (a): Applied Probability Models in Marketing

OIDD105 (c): Developing Tools for Data Access and Analysis

OIDD201 (o): Technology Management, Information and the Digital Economy

OIDD215 (a,c): Intro to Analytics and the Digital Economy

OIDD220 (a,o): Introduction to Operations Management

OIDD224 (o): Analytics for Service Operations

OIDD236 (o): Scaling Operations in Technology Ventures

OIDD245 (a, c, o): Advanced Analytics and the Digital Economy

OIDD255 (a, c): A.I., Data, and Society

OIDD311 (c): Business Computer Languages

OIDD314 (c, a): Enabling Technologies

OIDD 315 (a, c): Databases for Analytics

OIDD319 (a, c): Advanced Decision Systems

OIDD321 (o): Management Science

OIDD325 (o): Thinking with Models

OIDD353 (o): Mathematical Models in Finance

OIDD 469 (a,c): Advanced Information Strategy and Economics

STAT405 (a,c): Statistical Computing with R (0.5 CU course)

STAT410 (c): Data Collection & Acquisition

STAT422 (a,c): Predictive Analytics (0.5 CU course)

STAT430: Probability

STAT433: Stochastic Processes

STAT435 (a,c): Forecasting Methods for Management (Note: STAT 435 will not be offered in Fall 2022)

STAT442 (a): Bayesian Data Analysis

STAT470 (a,c): Data Analytics and Statistical Computing

STAT471 (a,c): Modern Data Mining

STAT474 (a): Modern Regression for the Social, Behavioral and Biological Sciences

STAT475 (a,c): Sample Survey Design

STAT/OIDD477 (a,c): Intro to Python for Data Science

STAT520 (a): Applied Econometrics I


+ Students can count only one of the two courses (CIS419/519 or 520) towards the Business Analytics concentration.

Business Analytics Joint Concentration Advisors

Sergei Savin (OIDD)  –  JMHH 570  –  215-898-1175  –
Dr. Richard Waterman (STAT) – JMHH 443 –

See the Wharton Customer Analytics Initiative ( for a collaborating venture, which offers opportunities for students with Business Analytics skills.