Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

What I learned from teaching 1,500 analytics students

Jerrard Gaertner (Ryerson University)
5:25pm6:05pm Wednesday, September 27, 2017
Enterprise adoption, Strata Business Summit
Location: 1A 18 Level: Advanced
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Senior managers, IT managers, corporate audit and risk managers, human resources, data scientists, big data project managers, and training personnel and teachers

Prerequisite knowledge

  • A basic understanding of the corporate, academic, and government big data ecosystems
  • Experience implementing big data and analytic initiatives at a management level

What you'll learn

  • Explore takeaways learned over the course of teaching 1,500 students


Sometimes, people can become so focused on technology, data, statistics, modeling, or other fascinating and important problems before them that they forget the world is not their big data playground. Quite the opposite. In fact, most of the real world misunderstands or fears what data scientists do (or, more often, just doesn’t care).

Jerrard Gaertner has taught about 1,500 adult learners at the University of Toronto School of Continuing Studies over the past four years through the Management of Enterprise Data Analytics program. Smart, mostly employed, ambitious, and intellectually engaged, these students come from a wide variety of industries, have diverse academic and employment backgrounds, and are for the most part anxious to share their experiences, both positive and negative, with their classmates. Although the statistician in Jerrard recognizes that this is a nonrepresentative, self-selecting, geographically limited cohort, the social scientist, organizational psychologist, technology strategist, and security auditor nevertheless sees an incredibly valuable richness in the combined experience of these individuals.

Jerrard shares stories he learned about everything from hyped-up expectations and internal sabotage to organizational streamlining and creating transformative insight. He covers big data projects, predictive analytics, organizational intransigence and subsequent liberation, fearful technologists, and immensely grateful patients and demonstrates how to reverse-engineer a big data job posting (for fun). Along the way, Jerrard explains why some of his students become so concerned about the ethical risks of prediction that they joined political or advocacy groups and summarizes some of the key factors underlying the high failure rates and slow penetration and progress of data-driven decision making. And of course, he will also try to entertain you.

Photo of Jerrard Gaertner

Jerrard Gaertner

Ryerson University

Jerrard Gaertner is Adjunct Professor of Compputer Science at Ryerson University in Toronto, Canada. He is also co-developer and lead instructor for big data education at the University of Toronto School of Continuing Studies.

Jerry is co-founder and President of Managed Analytic Services Inc. and a CPA, CA and CGEIT.

Jerry is a published author of three books and a graduate of MIT.