Parachutes dorés des grands patrons : atterrissage difficile pour le MEDEF et le gouvernement sur twitter | DATA VISUALIZATION & SOCIAL NETWORK ANALYSIS

Comme Libération l’a bien rappelé le 1er septembre, la rémunération des patrons en France, et notamment leurs bonus d’arrivée ou leur « retraite chapeau », fait régulièrement polémique. En mars 2013, les Suisses ont ainsi voté une limitation des hauts revenus, largement popularisée par la polémique née des 58,5 millions d’euros de prime de départ de l’ancien…

Why data quality matters—now more than ever

Not long ago, obtaining data for a GIS-based project was an arduous task. Because great time and effort was involved with either creating your own data or obtaining data that someone else created, you had to think carefully about the quality of the data that would go into your project. While it can still be cumbersome to obtain data at specific scales for specific areas, cloud-based data services, crowdsourced maps and databases and real-time streaming make it easy for anyone to obtain vast amounts of data in a short amount of time. In an environment where so much data is available, is data quality still of concern? I believe that yes, data quality does matter. In fact, because it is so easy to obtain data nowadays, and with the advent of crowdsourcing and cloud-based GIS, I submit that data quality considerations actually matter now more than ever. Consider the following three examples that focus on criticizing, analyzing and scaling your data.

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Le Big Data en un claquement de doigt !

« On entend beaucoup de choses sur les différentes méthodes de rentabilisation des données. En revanche, il est primordial de faire le bon choix d’infrastructure pour héberger et gérer le Big Data au cours des dix prochaines années.
Cependant, dix ans, c’est très long. En matière de Big Data, le contexte est encore mal défini, sans compter qu’il ne cesse d’évoluer. Il n’est pas surprenant que l’on peine à savoir comment procéder pour faire de cette innovation technologique un outil exploitable.
Le Big Data peut servir à établir des corrélations ponctuelles. Toutefois, comme l’indique Tim Hartford, correspondant du Financial Times à qui l’on doit l’expression de « pot d’échappement numérique », il n’offre aucune théorie à tester, et il peut être facile de confondre corrélation et cause. »

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15 Most Read Data Science Articles in 2015. So far … | Data Science Weekly Blog

« We’ve compiled the latest set of « most read » articles from the Data Science Weekly Newsletter. This is what is most popular thus far in 2015 – a mix of interesting applications of data science, advice on how best to get into the field, and unique explanations of some of the core concepts / techniques… »

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Don’t Just Get Your Data On; Get Your Data Right at Splunk .conf2015!

« Data: We’re swimming in it.

There is so much data on the Web, inside our organizations, with our partners … security and threat teams must sort through this data to find emerging threats to their organizations. This is hard enough given the plethora of data available, but even more complicated without any context to the information that makes up the intelligence that informs a threat program. »

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Don’t Just Get Your Data On; Get Your Data Right at Splunk .conf2015!

« Data: We’re swimming in it.

There is so much data on the Web, inside our organizations, with our partners … security and threat teams must sort through this data to find emerging threats to their organizations. This is hard enough given the plethora of data available, but even more complicated without any context to the information that makes up the intelligence that informs a threat program. »

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