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).
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:
- Data collection (c): methods for acquiring and manipulating data
- Advanced data analysis (a): working with data sets in a computing environment
- 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
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
LGST242x: 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
OIDD255x (a, c): A.I., Data, and Business.
OIDD311 (c): Business Computer Languages
OIDD314 (c, a): Enabling Technologies
OIDD319: Advanced Decision Systems
OIDD321 (o): Management Science
OIDD325 (o): Thinking with Models
OIDD353 (o): Mathematical Models in Finance
OIDD380: Operations Strategy Practicum
(a,c): AI, Data, and Society (currently offered as OIDD 399)
OIDD410 (a): Data Mining for Business Intelligence
STAT405 (a,c): Statistical Computing with R (0.5 CU course)
STAT422 (a,c): Predictive Analytics (0.5 CU course)
STAT435 (a,o): Forecasting Methods for Management
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
See the Wharton Customer Analytics Initiative (http://www.wharton.upenn.edu/wcai/) for a collaborating venture, which offers opportunities for students with Business Analytics skills.