EXECUTIVE EDUCATION

Business Analytics: From Data to Insights

Join this program and learn how to drive strategy and make better decisions with data

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Course Dates

STARTS ON

May 13, 2021

Course Duration

DURATION

3 months, online
6-8 hours per week

Course Duration

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.

$274.3 billion

IDC predicts analytics and big data market will reach $274.3 billion in revenue by 2022.

Source: Business Wire

55%

According to a 2020 Sisense COVID-19 survey, 55% of companies used data to improve efficiency during the pandemic while 47% relied on it to improve customer interactions and 45% used it to predict business outcomes.

Source: Sisense

80%

of the content streamed on Netflix is driven by analytics — specifically its recommendation engine.

Source: Wired UK

Who Is This Program For?

The Business Analytics program is designed to give participants an understanding of how to look at data and identify insights, improve their ability to make long-term predictions, and prescribe future actions to help make better business decisions.

The program is ideal for:

C-suite executives looking to keep pace with current trends, use business analytics as a strategic advantage, and make more data-backed decisions.

Mid- to senior-level managers looking to learn how analytics can help improve performance within their functional area while impacting business and growing in their roles.

Analysts who want to understand the business implications of analytics, better equip themselves to draw business relevant insights, and grow in their career.

Consultants seeking to offer better insights to their clients that are based on the latest ideas in business analytics, and learn structured approaches of problem solving through analytics.

  • Account Managers
  • CEOs
  • Executive Directors
  • Product Managers
  • Assistant Directors
  • Chief Marketing Officers
  • Financial Analysts
  • Business Analysts
  • CIOs
  • Vice Presidents
  • Consultant
  • Project Manager
  • Operations Manager
  • Business Development Manager
  • Finance Director

Participant Testimonials

Johnny Queck

"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

Damien Smith

"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

Pauline Francis

"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

Neil Gomes

"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

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Frameworks

Delivered via video lectures

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Real-World Examples

Delivered through a combination of video and live online lectures

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Applications to Data Sets

Learn through individual assignments and feedback

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Debrief of Learnings

Delivered through a combination of recorded and live video lectures

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4 Live Teaching Sessions by Wharton Faculty

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1 Data Analytics Simulation

Program Modules

Orientation Module:

Orientation and Introduction to Business Analytics

Module 1:

Descriptive Analytics: Gathering Insights

Identify effective methods for collecting data on customer behavior and use it to make better decisions for your business.

Module 2:

Descriptive Analytics: Describing and Forecasting Future Events

Learn how to use historical data such as trends and consumption patterns to estimate forecasts for the future.

Module 3:

Predictive Analytics: Making Predictions Using Data

Choose the right tool for decision-making to create future business strategies and determine the kinds of predictions you can make to create future strategies.

Module 4:

Predictive and Prescriptive Analytics: Application and Toolkit

Apply optimization models to specific business challenges with low uncertainty and determine the most favorable outcome for your business.

Module 5:

Predictive Analytics: Tools for Decision Making

Interpret and visualize the results of simulation models to evaluate complex business decisions in uncertain settings.

Module 6:

Predictive Analytics: Using Data to Predict Employee Performance

Use data analytics to derive insights into the key components of the staffing cycle for your business — hiring, internal mobility, and attrition.

Module 7:

Prescriptive Analytics: Providing Recommendations to Change Behavior

Write prescriptions for data-driven decision-making for your organization using optimization models.

Module 8:

Prescriptive Analytics: Determining the Most Favorable Outcomes

Determine the most favorable outcome for a business decision using decision trees in conjunction with optimization and simulation.

Module 9:

Application of Analytics for Business

Explain important components of different use cases of analytics in business and create a plan to put data to work in your organization.

Orientation Module:

Orientation and Introduction to Business Analytics

Module 5:

Predictive Analytics: Tools for Decision Making

Interpret and visualize the results of simulation models to evaluate complex business decisions in uncertain settings.

Module 1:

Descriptive Analytics: Gathering Insights

Identify effective methods for collecting data on customer behavior and use it to make better decisions for your business.

Module 6:

Predictive Analytics: Using Data to Predict Employee Performance

Use data analytics to derive insights into the key components of the staffing cycle for your business — hiring, internal mobility, and attrition.

Module 2:

Descriptive Analytics: Describing and Forecasting Future Events

Learn how to use historical data such as trends and consumption patterns to estimate forecasts for the future.

Module 7:

Prescriptive Analytics: Providing Recommendations to Change Behavior

Write prescriptions for data-driven decision-making for your organization using optimization models.

Module 3:

Predictive Analytics: Making Predictions Using Data

Choose the right tool for decision-making to create future business strategies and determine the kinds of predictions you can make to create future strategies.

Module 8:

Prescriptive Analytics: Determining the Most Favorable Outcomes

Determine the most favorable outcome for a business decision using decision trees in conjunction with optimization and simulation.

Module 4:

Predictive and Prescriptive Analytics: Application and Toolkit

Apply optimization models to specific business challenges with low uncertainty and determine the most favorable outcome for your business.

Module 9:

Application of Analytics for Business

Explain important components of different use cases of analytics in business and create a plan to put data to work in your organization.

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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

Image of a group of people enjoying coffee to potray the Starbucks case study

Consumer Packaged Goods

How is Starbucks identifying which customers to give deals to in order to maximize return on investment (RoI)?

image of credit and debit cards on a table to potray American Express case study

Financial Services

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

A laptop screen with the Netflix window open next to a coffee mug on a bed to potray the Netflix case study

Media

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

Image of a lady reading a magazine at a supermarket aisle to potray the Time magazine case study

Retail

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

Image of the entry of a giant shopping mall to potray the Kohl's case study

Apparel

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

Image of packed carton boxes on a factory belit to potray the Amazon case study

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

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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