Data Day Mexico

Mexico City March 15, 2018
Tags: Data mba, Machine learning, Data engineering, Non-enterprise

CFP closed at  January 10, 2018 20:00 UTC

Data Day Mexico is a one-day conference focused on strategy, practices and tools for analyzing and managing data at scale. It will take place in Mexico city on March 15th, 2018 and will host an audience of 300-350 data professionals.

CFP Description

Data Day Mexico is the premier event for data professionals in Mexico. This is the 3rd straight year we organize it and expect an audience of 300-350 data professionals.

We have 3 main tracks, for our 3 major segments of audience:

  • Data Science MBA: Sessions for business executives looking for strategy and lessons learned about leading data science initiatives in enterprise contexts. We highly value proposals focused on specific verticals (retail, telco, media, manufacturing, etc).
  • Applied Data Science & Machine Learning: Sessions targeted to data professionals, focused on best practices, techniques and tools for data science.
  • Big Data Engineering: Sessions targeted to software engineers focused on best practices, techniques and tools to implement code & infrastructure to support processing of complex models & big data.

We will also have an extra track (Machine Learning + Human Inspiration) focused on the application of machine learning in non enterprise fields like arts, media, citizenship.

Community sessions are non-commercial. They should not be focused on promoting the offering or achievements of specific companies. If you are interested in this option, please contact so that we may provide you with information on how to have a sponsored session.

Please make sure that in your profile you include the following information about yourself: Current company & title; URL with information about you (personal page, linkedin, or similar); Link to previous talks you have given (slideshare, videos, etc).

Also, please use the tags to let us know which track you think your session would fit in.

Attendees (4)