EXECUTIVE EDUCATION

Business Analytics: Data-driven Decision Making

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Course Dates

STARTS ON

August 12, 2021

Course Duration

DURATION

6 weeks, online
4-6 hours/week

Course Duration

Decipher the Data to Make Better Business Decisions

Analyzing data and putting it to work for you and your business is an essential skill for executives today. But if you are not as fluent as you need to be in data and analytics, you’re not alone. According to The Data Literacy Index from Qlik, just 24 percent of the global workforce feels confident in reading, working with, analyzing, and arguing with data. You can close that competency gap by gaining the skills to transform your organization into a data-driven enterprise.

This is not just about adding to your own professional skill set. Gartner reports that 80 percent of organizational leaders have a goal of initiating a deliberate plan to improve the data literacy of their workforce at large. Position yourself and your company to advance your data literacy and confidently lead a data-driven corporate culture.

#1 in Canada for Open Enrolment

Source: The Financial Times 2020

What You'll Get

  • Improved data literacy, the ability to communicate effectively with data analysts to understand when to use (and how to interpret) descriptive, predictive, and prescriptive analytics
  • Expert guidance on evaluating various data analytics tools, such as dashboards, machine learning, prediction models, and regression analysis
  • Techniques to apply scientific thinking to business, such as examining cause and effect in data analysis and designing an experiment
  • A deeper understanding of how to build a data-driven organization, including managing privacy concerns and developing strategies for cultivating evidence-based decision-making

Program Curriculum

Each module is designed to help you craft the narrative for your company’s data literacy by improving your own data fluency and gaining an understanding of the business value quality data and expert analytics can create for your business.

Module 1:

Data Basics

Dive into the fundamentals by comparing the various types of data analysis, examining variables, and analyzing the impact of sample size and sample bias.

Module 2:

Dashboarding

Do you know your dashboards? Understand the applications of data analytics dashboards and the use of conditional averages, distributions, regression to the mean, and hypothesis testing to devise Key Performance Indicators (KPIs)

Module 3:

Introduction to Prediction

If futurecasting appeals to your strategic side, it’s critical to understand predictive analysis, the construction of a prediction model, the application of machine learning and AI to prediction, and the strategic implications of prediction.

Module 4:

Regression

Perhaps the single most essential tool in statistical modeling, regression is central to data literacy. Learn what regression does, how it fits into prediction, and what questions to ask data analysts (and yourself).

Module 5:

Scientific Thinking in Business: Prescriptive Analysis

How do you mold raw data into a business strategy? Examine cause and effect in data analysis, design an experiment, analyze causal inference without experiments, and be prepared to prescribe a response to the likely results.

Module 6:

Building a Data-Driven Organization

Widen your view of data literacy to your whole workforce. Develop an organizational model for a question-driven approach to data analysis, understand privacy concerns, and formulate a strategy to build an evidence- and learning-based corporate culture.

Module 1:

Data Basics

Dive into the fundamentals by comparing the various types of data analysis, examining variables, and analyzing the impact of sample size and sample bias.

Module 4:

Regression

Perhaps the single most essential tool in statistical modeling, regression is central to data literacy. Learn what regression does, how it fits into prediction, and what questions to ask data analysts (and yourself).

Module 2:

Dashboarding

Do you know your dashboards? Understand the applications of data analytics dashboards and the use of conditional averages, distributions, regression to the mean, and hypothesis testing to devise Key Performance Indicators (KPIs)

Module 5:

Scientific Thinking in Business: Prescriptive Analysis

How do you mold raw data into a business strategy? Examine cause and effect in data analysis, design an experiment, analyze causal inference without experiments, and be prepared to prescribe a response to the likely results.

Module 3:

Introduction to Prediction

If futurecasting appeals to your strategic side, it’s critical to understand predictive analysis, the construction of a prediction model, the application of machine learning and AI to prediction, and the strategic implications of prediction.

Module 6:

Building a Data-Driven Organization

Widen your view of data literacy to your whole workforce. Develop an organizational model for a question-driven approach to data analysis, understand privacy concerns, and formulate a strategy to build an evidence- and learning-based corporate culture.

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Program Experience

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Try-it activities

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Peer discussion groups

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Crowdsourcing activities

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Quizzes

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Real-world applications assignments

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Live Webinar

Who Should Attend

This program is designed for business leaders who engage with data teams and output reports and want to have more meaningful conversations with their analytics team, integrating data into their decision-making and also their corporate culture. This program is particularly applicable for:

  • C-Suite Executives from any industry with access to a massive data stream — such as IT services, banking and financial services, and health care — seeking to learn the language of data, to use analytics to strategic advantage, and to develop an analytics roadmap for their organization.
  • Mid-to Senior-Level Managers, such as general manager, corporate director, head of marketing, or head of strategy, seeking to garner insights from data and looking to gain a practical understanding of the applications of analytics to initiate new projects or launch new business ideas.

Program Faculty

Faculty Member Avi Goldfarb

Avi Goldfarb

Rotman Chair in Artificial Intelligence and Healthcare, Professor of Marketing, Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, Research Associate at the National Bureau of Economic Research

As Rotman Chair in Artificial Intelligence and Healthcare and Professor of Marketing at University of Toronto’s Rotman School of Management, Avi Goldfarb’s research focuses on the opportunities and challenges of the digital economy. Along with Ajay Agrawal and Joshua Gans, Dr. Goldfarb is the author of The Globe and Mail bestselling book Prediction Machines: The Simple Economics of Artificial Intelligence. He has published more than 70 academic articles in a variety of outlets on the topics of marketing, statistics, law, computing, and economics. This work has been discussed in White House reports, Congressional testimony, European Commission documents, The Economist, The Globe and Mail, the National Post, CBC Radio, National Public Radio, Forbes, Fortune, The Atlantic, The New York Times, the Financial Times, The Wall Street Journal, and elsewhere.

Dr. Goldfarb holds a Ph.D. and M.A. in Economics from Northwestern University and a B.A. in Economics from Queen’s University.

Certificate

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

Certificate

Upon successful completion of the program, you’ll earn a digital certificate of completion from the Rotman School of Management. This program counts toward a Rotman Excellence in Executive Leadership Certificate.

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

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