News June 22nd 2015

Ekimetrics sponsors the Data Science Game

Data Science Game ENSAE Paristech Ekimetrics Google
Data Science Games: 2 days of competition in a dream castle near Paris to prove your worth to the ever growing Big Data community.

ENSAE ParisTech and ParisTech, along with Ensta ParisTech and Telecom ParisTech, invite all data science students from Universities all around the world to participate to the 1st edition of the Data Science Game.

By solving a data driven issue, students will be able to enlighten their data science expertise in a both competitive and friendly spirit.

The competition was supported by major partners and sposors such as: Google Inc, Ekimetrics and Capgemini

Because data are both major input and output in our connected lives, because data science students are the builders of tomorrow and because we believe that they deserve to be in the limelight. Ekimetrics was very happy to be part of the first international data science event in Paris. 

Here after a picture of Paul Seguineau, parnter at Ekimetrics giving the 5th price to the Imeprial College London

Paul Seguineau Partner at Ekimetrics Giving Data science Game price to imperial College

Here is an Ekimetrics Infographic of the Ideal Data Scientist

The Ideal Data Scientist Data Science Big Data

 

Thought Leadership July 10th 2019

McDonald's France : business strategy, behavioural analysis & big data

Whether I’m in class or talking to friends, it is often difficult to explain to them what the meta-data in their daily lives can do. It is easy to imagine how big data is used in scientific calculations of meteorological models or for managing transport, but it is harder to see how it can be used in our daily lives.
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How to combine business approaches, advanced statistics, and technology?

It is sometimes difficult to create a link between highly sophisticated statistical approaches and business reality. The transformation of data into value is an art that needs to combine three different pillars: business understanding, advanced statistics and technology. This triangular approach needs to be adopted by all machine learning projects.