Business Analytics: From Data To Insights

Wharton’s three-month online certificate program — Business Analytics: From Data to Insights — provides managers and leaders an understanding of how analytics can help improve their decision-making process. This program will help you look at data and identify insights, improve your ability to make predictions for the long term, and prescribe future actions that help make better business decisions.

3 months, online
6–8 hours per week


December 6, 2018

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Why Study Business Analytics?


The amount of data doubles every three years as various digital sources continue to make information available.
Source: McKinsey & Company

1.5 Million

A significant shortage of managers and analysts who can effectively use analytical concepts to make decisions is predicted for 2018.
Source: McKinsey & Company


Three-quarters of companies are missing the skills and technology to make the best use of the data they collect.
Source: PWC

High-Impact Online Learning


Delivered via video lectures

Real-World Examples

Delivered through a combination of video and live online lectures

Applications to Data Sets

Learn through individual assignments and feedback

Debrief of Learnings

Delivered through a combination of recorded and live video lectures

Program Experience

4 Live Teaching Sessions by Wharton Faculty  •  1 Data Analytics Simulation

Program Modules

Orientation Module: Orientation and Introduction to Business Analytics

Module 1: Descriptive Analytics: Gathering Insights

Module 2: Descriptive Analytics: Describing and Forecasting Future Events

Module 3: Predictive Analytics: Making Predictions Using Data

Module 4: Predictive and Prescriptive Analytics: Application and Toolkit

Module 5: Predictive Analytics: Tools for Decision Making

Module 6: Predictive Analytics: Using Data to Predict Employee Performance

Module 7: Prescriptive Analytics: Providing Recommendations to Change Behavior

Module 8: Prescriptive Analytics: Determining the Most Favorable Outcomes

Module 9: Application of Analytics for Business

Methods and Tools

Data Collection Methods

  • Descriptive Data Collection: Surveys, Net Promoter Score (NPS), and Self-Reports
  • Passive Data Collection
  • Media Data Collection: Radio, Television, Mobile, etc.

A/B Testing

Correlation and Causation


  • Objective and Subjective
  • Strand or Seasonal Variation
  • Exponential Smoothing
  • Descriptive Statistics
  • Trends and Seasonality
  • New Product

Regression Analysis

Simulation Toolkit

  • Analysis ToolPak
  • Solver Optimization Tool

Data Visualization and Interpretation

Optimization Models

Decision Trees


Earn a digital Wharton certificate upon successful completion of the online program.

(This online certificate program does not grant academic credit or a degree from the Wharton School of the University of Pennsylvania. The certificate image is for illustrative purposes only and may be subject to change.)

Industry Examples

Consumer Packaged Goods
How is Starbucks identifying which customers to give deals to in order to maximize return on investment (ROI)?

Financial Services
How does American Express use social media data to predict whether you are going to give up your American Express card?

How is Netflix using metadata tagging to know what you watch and to create relevant content?

Why were stores either selling out of Time magazine or only selling a small fraction of their inventory?

How has Kohl’s been using analytics for smartphone targeting?

How could Amazon potentially ship before you buy?

Academic Director

Christopher D. Ittner, PhDSee Faculty Bio

EY Professor of Accounting; Chairperson, Accounting Department, The Wharton School

Research Interests: Cost accounting, intangible assets, performance measurement

Additional Faculty

Ron Berman, PhDSee Faculty Bio

Assistant Professor of Marketing, The Wharton School

Research Interests: Online marketing, entrepreneurship, marketing analytics, search engine marketing, game theory, industrial organization

Matthew Bidwell, PhDSee Faculty Bio

Associate Professor of Management, The Wharton School

Research Interests: Human resource management, knowledge workers, worker mobility

Eric T. Bradlow, PhDSee Faculty Bio

The K. P. Chao Professor; Professor of Marketing; Faculty Director, Wharton Customer Analytics Initiative; Chairperson, Wharton Marketing Department; Professor of Economics; Professor of Education; Professor of Statistics

Research Interests: Marketing research methods, missing-data problems, psychometrics

Peter Fader, PhDSee Faculty Bio

Frances and Pei-Yuan Chia Professor; Professor of Marketing, The Wharton School

Research Interests: Lifetime value of the customer, sales forecasting for new products, behavioral data

Noah GansSee Faculty Bio

Anheuser-Busch Professor of Management Science; Professor of Operations, Information and Decisions; Department Chairperson, The Wharton School

Research Interests: Service operations, stochastic processes, the control of queueing systems

Raghuram Iyengar, PhDSee Faculty Bio

Miers-Busch, W’1885 Professor, Professor of Marketing; Faculty Co-Director, Wharton Customer Analytics Initiative (WCAI), The Wharton School

Research Interests: Pricing, social influence, social networks

Sergei Savin, PhDSee Faculty Bio

Associate Professor of Operations, Information, and Decisions, The Wharton School

Research Interests: Capacity and patient flow management in health care operations, diffusion models for new products and services, revenue management

Senthil Veeraraghavan, PhDSee Faculty Bio

Professor of Operations, Information, and Decisions, The Wharton School

Research Interests: Empirical operations management, operations analytics, operations management, operations strategy, pricing and revenue management, service operations management, supply chain management