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Monday Mentor Minutes - Molly Ziske

https://spartanshelpingspartans.files.wordpress.com/2016/08/molly-ziske.mp3

Spartan Molly Ziske shares how she tells stories with research and data as a Senior Consumer Insights Manager.

Molly Ziske is currently a Senior Consumer Insights Manager for McCann Worldgroup Detroit. 127 more words

Forces in D3.js v4

A short demonstration of the various forces that are available in the latest version of D3.js. Following the update to version 4, there has been a significant change in the syntax for applying forces. 1,389 more words

Data Analytics

Basketball Paper Update

Everyone by now knows about this paper I wrote a few months ago: http://arxiv.org/abs/1604.05266

Using data science / machine learning methodologies, it basically showed that the most important factors in characterizing a team’s playoff eligibility are the opponent field goal percentage and the opponent points per game. 207 more words

Mathematics

T-Systems voorspelt aankomst en vertrek Deutsche Bahn-treinen met data-analytics

Vianen, 21 september 2016Deutsche Bahn gaat binnenkort een door T-Systems ontwikkeld systeem in gebruik nemen dat de aankomst- en vertrektijden van treinen voorspelt. Reizigers zien tot 90 minuten van tevoren hoe laat hun trein aankomt. 383 more words

Alle Persberichten

Daimler partners with NUS Enterprise to launch accelerator in Singapore

Source: Thetechportal

Singapore: German automaker Daimler has collaborated with NUS Enterprise to launch its Startup Autobahn accelerator programme in Singapore, as a part of the Mercedes-Benz producer’s initiative in Germany. 338 more words

Corporate Innovation

What makes a good data scientist?

Tom Breur

20 September 2016

Data Scientist is a term that DJ Patil coined in 2008, and that is now called “the sexiest job of the 21st century.” Apparently, when Hal Varian (Chief Scientist at Google) coined “statistician” the sexiest job of the 21st century, that wasn’t good enough. 704 more words

Data Analytics

Are You on the Data Offensive or Defence?

Understanding the different types of data positions – data offensive or data defence.

Companies are either on the data offensive or data defence – and organisations need to move to being on the offensive to actively take hold of data and make tangible use of it. 908 more words

Big Data