Putting Data Science in action for your organization

Jun 6, 2017 · Huizen, Netherlands

Meetup is part of the  Dutch Data Science Week

Theme: Putting Data Science in action for your organization. 

Data is the new oil of the organization. Data Scientists use algorithms and models to explore this data and discover valuable insights from it. But how do you put these insights into action and how can you take the next step in facilitating the decision making process

Program:

-Opening: Edwin van Unen, SAS

-Speaker 1: Tom Dogger, Notilyze - Data Science in decision making

How could Data Science help organizations make operational decisions and how could these decision be automated to scale up the organization? During this presentation the necessary steps to bring Data Science to an organization are shown using a real life client case. The case describes the strengths and pitfalls of analytics and how to create an analytics culture with the business that understands and utilizes new opportunities.

-Speaker 2: Tuba Islam, SAS - Don’t just build it, execute it!

By human nature, we always want to work on what we enjoy and what we are good at. However, when it comes to monetizing our work and bringing value to our organization, there might be a trade-off between our individual motives and the company goals. As data scientists, we wouldn’t mind spending hours with our favorite analytical tools trying to build perfect models, but putting those models in production quickly would bring the value to the organization. We will talk about the challenges and benefits of operationalizing analytical models including open source and how it would be possible to set up a complete process for execution and model management with minimum human intervention.  

- Speaker 3: Matthijs Wolters, SciSports - Data science serving football

In this presentation Scisports explains how data science creates value for their 2 flagship products:

SciSkill: Determines the value and potential of football players. The SciSkill helps us to find great and/or undervalued players by benchmarking them according to similar players.

BallJames: Automatically generates 3D data from video images of football matches. In the stadium, fourteen cameras are installed, which record all the movements on the field. BallJames then generates its own data such as the clearness, direction and speed of the passing, sprinting strength, jumping strength, player movements and how close the ball stays at the foot after a first touch

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