When I asked Bruno Aziza last year how he would best describe a data scientist, his answer still sticks with me today. “Think of a data scientist more like the business analyst-plus,” he told me. Part mathematician, part business strategist, these statistical savants are able to apply their background in mathematics to help companies tame their data dragons. But these individuals aren’t just math geeks, per se.
Shown are the favorite websites using self reported results of all registered users on DataScienceCentral. It is interesting to note that Kdnuggets continues to be a strong leader as a data aggregator for the community even among the biased sample of DataScienceCentral members. It is also impressive to see R with such a strong pressence.
I’m really looking forward to the upcoming session at Predictive Analytics World: Necessary Skills of the Quant Across Sectors
What makes a quant a true rockstar? What kind of soft skills, what kind of tech skills and background, and what portfolio of experience? With the organizational process behind predictive analytics – across business applications such as fraud and marketing – something of an art form, the requisite skills of key analytics staff are multidimensional and often hard to nail down. This expert panel will grab a hammer and start defining exactly what’s needed in this very particular workforce.
Today I found out the hard way that if you don’t block your search pages then google will drop your site fast. For more details, I followed this tutorial, http://www.feedthebot.com/block-unuseful-pages.html.