Online Certificate in Business Analytics: From Data to Insights

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 the analytics and big data market will reach $274.3 billion in revenue by 2022. (Source: Business Wire)
• 80% of the content streamed on Netflix is driven by analytics — specifically its recommendation engine. (Source: Wired UK)
• 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)

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 careers.
• 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

Program Modules

Orientation Module: 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.

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

Starbucks

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

American Express

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

Netflix

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?