10 Most Influential People in Data Analytics
Here is another list of 10 Most Influential People in Data Analytics, which includes (in alphabetical order) Dean Abbott, Mchael Berry, Tom Davenport, John Elder, Rayid Ghani, Anthony Goldbloom, Vincent Granville, Gregory Piatetsky-Shapiro, Karl Rexer, and Eric Siegel.
By Gregory Piatetsky, May 14, 2013.
Jiang (Jay) Zhou, Ph.D., author of Deep Data Mining blog, has come up with a list of 10 most influential people whose significant contributions have greatly enriched the data analytics community.
These 10 people, in alphabetical order of their last name, are
- Dean Abbott, @deanabb, President of Abbott Analytics, San Diego, CA.
- Michael Berry, a leading expert on business applications of data mining, Analytics Director at TripAdvisor for Business.
- Tom Davenport, a Visiting Professor at Harvard Business School, author of Competing on Analytics, co-founder of Int. Institute of Analytics.
- John Elder, founder and CEO of Elder Research, US largest data mining consultancy.
- Rayid Ghani, @rayidghani, at U. of Chicago and Edgeflip, was the Chief Data Scientist at Obama for America 2012 campaign.
- Anthony Goldbloom, @antgoldbloom, the founder and CEO of Kaggle.
- Vincent Granville, @analyticbridge, an expert in scoring technology, fraud detection and web traffic optimization, founder of AnalyticBridge and Data Science Central.
- Gregory Piatetsky-Shapiro, @kdnuggets, Analytics/Data Mining expert, the Editor of KDnuggets, co-founder of KDD, the leading conference on Knowledge Discovery and Data Mining, and ACM SIGKDD.
- Karl Rexer, Founder and President of Rexer Analytics, a leading expert on Analytics.
- Eric Siegel, founder of Predictive Analytics World and Text Analytics World, author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
Most of them (except Dean, Antony, and Michael) are Ph.Ds. See more details and description of their contribution at
I asked Jay how he came up with this list and he wrote
To select 10 most influential people in data analytics, the following considerations are taken into account regarding an individual's contribution.
1. The contribution is significant.
2. The contribution is active/regular.
3. A large number of people are impacted by the contribution.
4. The focus is on the non-academic field.
I performed online research first to find qualified people. KDnuggets.com, other websites of social networking, data analytics conferences, consulting firms, and Amazon are just a few examples of good sources for information. I also took advantage of my own network. Being in the industry for 15 years, I have known many great data analytics professionals. They provided me with many names of qualified people. After I compiled a preliminary list, I sent it to a number of experts for their feedback. The final list was the result of several iterations.