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 1010) and STAT (STAT 1010 and STAT 1020), 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.
Approved Undergraduate Courses:
ACCT2700 (a,c): Predictive Analytics Using Financial Disclosures
BEPP2800 (a): Applied Data Analysis
BIOL4470 (a): Biological Data Analysis
CIS3990: The Science of Data Ethics
†CIS4190/5190 (a): Applied Machine Learning
CIS4500 (c): Database and Information Systems
†CIS5200 (a): Machine Learning
CIS5450 (a,c): Big Data Analytics
COMM3130 (a,c): Computational Text Analysis for Communication Research
ESE3010: Engineering Probability
ESE3050 (a): Foundations of Data Science
ESE3060 (a, o): Deep Learning: A Hands-on Introduction
ESE4020/5420 (a): Statistics for Data Science
EST5030 (o): Simulations, Modeling, and Analysis
ESE5040 (o): Introduction to Linear, Nonlinear and Integer Optimization
ESE5060 (o): Introduction to Optimization Theory
FNCE2050 (o): Investment Management
FNCE2170 (a,o): Financial Derivatives
FNCE2370 (a,c): Data Science for Finance
FNCE2800 (a): Fin-Tech
HCMG3570 (a,c): Health Care Data and Analytics
LGST2420: Big Data, Big Responsibilities: The Law and Ethics of Business Analytics
MGMT2930 (a,c): People Analytics
MKTG2120 (a): Data and Analysis for Marketing Decisions
MKTG2710 (a): Models for Marketing Strategy
MKTG3090 (a,c): Experiments for Business Decision Making
MKTG3520 (a,c): Marketing Analytics
MKTG4760 (a): Applied Probability Models in Marketing
OIDD1050 (c): Developing Tools for Data Access and Analysis
OIDD2010X (o): Technology, Online Business Model Innovation, and Valuation
OIDD2150 (a,c): Intro to Analytics and the Digital Economy
OIDD2200 (a,o): Introduction to Operations Management
OIDD2210 (o): Optimization and Analytics (formerly OIDD 3210)
OIDD2240 (o): Analytics for Service Operations
OIDD2360 (o): Scaling Technology Ventures: Aligning Operations with Strategy
OIDD2450 (a,c,o): Analytics and the Digital Economy
OIDD2550 (a,c): AI, Data, and Society
OIDD3110 (c): Business Computer Languages
OIDD3140 (a,c): Enabling Technologies
OIDD3150 (a,c): Databases for Analytics
OIDD3190: (a,c): Advanced Decision Systems
OIDD3250 (a,c,o): Thinking with Models
OIDD3530 (o): Mathematical Models in Finance
OIDD3800: Operations Strategy Practicum
OIDD4100 (a): Data Mining for Business Intelligence
OIDD4690 (a,c): Advanced Information Strategy and Economics
OIDD5250 (a,c,o): Thinking with Models: Business Analytics for Energy and Sustainability
REAL3700 (a,c): Real Estate Data Analytics
PSCI1800 (a,o): Introduction to Data Science
STAT4050 (a,c): Statistical Computing with R (0.5 CU course)
STAT4100 (c): Data Collection and Acquisition: Strategies and Platforms (0.5 CU course)
STAT4220 (a,c): Predictive Analytics (0.5 CU course)
STAT4230 (a): Applied Machine Learning in Business
STAT4300: Probability
STAT4310 (a): Statistical Inference
STAT4330: Stochastic Processes
STAT4350 (a,c): Forecasting Methods for Management
STAT4420 (a): Introduction to Bayesian Data Analysis
STAT4700 (a,c): Data Analytics and Statistical Computing
STAT4710 (a,c): Modern Data Mining
STAT4740 (a): Modern Regression for the Social, Behavioral and Biological Sciences
STAT4750 (a,c): Sample Survey Design
STAT/OIDD4770 (a,c): Intro to Python for Data Science (0.5 CU course)
STAT5200 (a): Applied Econometrics I
+ Students can count only one of the two courses (either CIS4190/5190 or CIS5200) towards the Business Analytics concentration.
Business Analytics Joint Concentration Advisors
Prof. Sergei Savin (OID) – JMHH 546 – 215-898-1175 – savin@wharton.upenn.edu
Prof. Richard Waterman (STAT) – SCC 109C – waterman@wharton.upenn.edu
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.