Business Analytics: From Data to Insights

Formulate data-driven business decisions that lead your company towards success

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Course Date

STARTS ON

November 16, 2021

Course Duration

DURATION

3 months, online
6-8 hours per week

Course Fee

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

Portrait image of Justin Teo against a gray background

Data analytics have never been my strongest skill so I am truly glad to be exposed to a lot of new concept and applications that can help businesses perform better.  And in the process making a lot of meaningful and long-lasting relationships with my cohort of classmates. 

— Justin Teo, Chief Digital Officer

Portrait photograph of Francisco Márquez 

The Wharton Executive Education school provided me the right methods, tools, and applications to learn across 3 pillars: Predictive, Prescriptive, and Descriptive Analytics. After several weeks of work and study, I'm very excited to start formulating data-driven recommendations that lead my company toward success in my day-to-day activities.

— Francisco Márquez, Manager, Supply Network

I have always had a passion and interest for numbers and an analytical mindset, so this summer, I decided to enroll in Wharton Online Business Analytics: From Data to Insights to gain a high-level understanding of how analytics can help business stakeholders make decisions. I am so glad I did! I thoroughly enjoyed learning about descriptive, predictive, and prescriptive analytics from some of the most talented faculty in the industry and alongside classmates from around the world. Data now more than ever, is critical to all markets and I am now more prepared to provide insight to my future employers.

— Haley Mathewson, Consultant Associate

Portrait photograph of Charlene Ren

It is my great pleasure to successfully complete the Business Analytics: From Data to Insights course at Wharton Online for the past 3 months. This course has taught me various analytics tools and methods that could help optimize business operations. In addition, I have been practicing data-driven decision-making skills through case studies and online simulations. The biggest takeaway is definitely knowing how to analyze massive data using Excel as well as the add-in packages. The program also gives me the opportunity to network with professors and classmates from distinctive industries who have brought tons of creative ideas to the course. Therefore, I am extremely grateful for this program for benefiting both my academic and professional development.

— Charlene Ren, Academic Project Consultant

Portrait photograph of Mahalakshmi Viswanathan

As the name suggests, getting more insights in handling Big Data & analysing them to complement the right decision-making is a skillset that everyone needs to acquire in the fast-changing digital world. The Wharton Business School (known for its analytics courses), provides an outlook of how data mining is critical in determining the short-term & long-term strategic intervention for a given business in a VUCA environment. This course helped me familiarise with various analytical tools viz. descriptive, predictive & prescriptive analytics, through big datasets & live simulation models. Thanks to the course director, faculty members & peers for making this course interactive & interesting !!

— Mahalakshmi Viswanathan, Business Director

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

Faculty Member Christopher D. Ittner

Christopher D. Ittner

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

Faculty Member Peter Fader

Peter Fader

Frances and Pei-Yuan Chia Professor; Professor of Marketing

Faculty Member Raghuram Iyengar

Raghuram Iyengar

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

Faculty Member Senthil Veeraraghavan

Senthil Veeraraghavan

Professor of Operations, Information and Decisions

Faculty Member Sergei Savin

Sergei Savin

Associate Professor of Operations, Information and Decisions

Faculty Member Ron Berman

Ron Berman

Assistant Professor of Marketing

Faculty Member Noah Gans

Noah Gans

Anheuser-Busch Professor of Management Science

Faculty Member Eric Bradlow

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

Faculty Member Matthew Bidwell

Matthew Bidwell

Associate Professor of Management

Certificate

Example image of certificate that will be awarded after successful completion of this program

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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