EXECUTIVE EDUCATION

Business Analytics: From Data to Insights

Join this program to learn in-depth tools and strategies

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Course Dates

STARTS ON

March 24, 2021

Course Duration

DURATION

3 months, online
6-8 hours per week

Course Duration

PROGRAM FEE

US$2,600 or get US$260 off with a referral

Course Information Flexible payment available
Course Information Special group enrollment pricing

Welcome

To claim your US$260 program fee coupon for Business Analytics: From Data to Insights, please complete the information form.

Why Study Business Analytics?

Wharton's three-month online program — Business Analytics: From Data to Insights — arms managers and leaders with the tools needed to break away from the pack. Take the opportunity to turn data into a competitive advantage.

2X

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

75%

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

SOURCE: PWC
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Who Is This Program For?

This online program is ideal for managers and leaders who wish to learn how analytics can help improve their decision-making processes. Business Analytics: From Data to Insights will give participants an understanding of how to look at data and identify insights, improve their ability to make longterm predictions, and prescribe future actions to help make better business decisions. Participants come from a wide range of industries, job functions, and management levels.

Participants by Job Function Include:

  • Account Managers
  • CEOs
  • Executive Directors
  • Product Managers
  • Assistant Directors
  • Chief Marketing Officers
  • Financial Analysts
  • Portfolio Managers
  • Business Analysts
  • CIOs
  • Investment Directors
  • Vice Presidents

Participant Testimonials

"The course provided a good overview of how analytics can be applied across various entities within an organisation such as supply chain, HR, manufacturing, etc."

— Johnny Queck, Regional Director – ASEAN, bioMérieux, Singapore

"Learning the many analytical models will help me in my day–to–day work. This is a skill that I have been missing for years. I feel confident I can work smarter going forward."

— Damien Smith, Airport Retail Manager, Aer Rianta International, Ireland

"The teaching faculty was excellent and the pace of how they presented the material in each module was perfect. The combination of Wharton-quality instruction and Emeritus delivery was seamless."

— Pauline Francis, Partner, B2B CFO, USA

"The videos and practical examples were the best part. The faculty were also world-class and explained concepts really well."

— Neil Gomes, Chief Digital Officer and Senior VP, Thomas Jefferson University, USA

Your Learning Experience

Frameworks

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

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

Orientation Module:

Orientation and Introduction to Business Analytics

Module 5:

Predictive Analytics: Tools for Decision Making

Module 1:

Descriptive Analytics: Gathering Insights

Module 6:

Predictive Analytics: Using Data to Predict Employee Performance

Module 2:

Descriptive Analytics: Describing and Forecasting Future Events

Module 7:

Prescriptive Analytics: Providing Recommendations to Change Behavior

Module 3:

Predictive Analytics: Making Predictions Using Data

Module 8:

Prescriptive Analytics: Determining the Most Favorable Outcomes

Module 4:

Predictive and Prescriptive Analytics: Application and Toolkit

Module 9:

Application of Analytics for Business
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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

Forecasting

  • 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

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?

Media

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

Retail

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

Apparel

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

Technology

How could Amazon potentially ship before you buy?

Program Faculty

Christopher D. Ittner

Faculty Director, EY Professor of Accounting; Chairperson, Accounting Department

Peter Fader

Frances and Pei-Yuan Chia Professor; Professor of Marketing

Raghuram Iyengar

Miers-Busch, W’1885 Professor, Professor of Marketing; Faculty Director, Wharton Customer Analytics (WCA)

Senthil Veeraraghavan

Professor of Operations, Information and Decisions

Sergei Savin

Associate Professor of Operations, Information and Decisions

Ron Berman

Assistant Professor of Marketing

Noah Gans

Anheuser-Busch Professor of Management Science

Eric Bradlow

The K. P. Chao Professor; Professor of Marketing; Vice Dean, Analytics at Wharton; Chairperson, Wharton Marketing Department; Professor of Economics; Professor of Education; Professor of Statistics, The Wharton School

Matthew Bidwell

Associate Professor of Management

Christopher D. Ittner

Faculty Director, EY Professor of Accounting; Chairperson, Accounting Department

Peter Fader

Frances and Pei-Yuan Chia Professor; Professor of Marketing

Raghuram Iyengar

Miers-Busch, W’1885 Professor, Professor of Marketing; Faculty Director, Wharton Customer Analytics (WCA)

Senthil Veeraraghavan

Professor of Operations, Information and Decisions

Sergei Savin

Associate Professor of Operations, Information and Decisions

Ron Berman

Assistant Professor of Marketing

Noah Gans

Anheuser-Busch Professor of Management Science

Eric Bradlow

The K. P. Chao Professor; Professor of Marketing; Vice Dean, Analytics at Wharton; Chairperson, Wharton Marketing Department; Professor of Economics; Professor of Education; Professor of Statistics, The Wharton School

Matthew Bidwell

Associate Professor of Management

Certificate

Certificate

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

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All certificate images are for illustrative purposes only and may be subject to change at the discretion of the Wharton School.

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