This newsletter contains three sections: announcements from sponsors (at the top), featured contributions from the Data Science Central community, and valuable resources for big data, data science and analytic practitioners (at the bottom).
Added by Vincent Granville on November 30, 2012 at 8:30am — No Comments
Without having anyone working (reporting to) them, according to the Wall Street Journal.
Live Simulcast Panel Discussion on Dec. 12.
|Everybody has an opinion on Santa Claus. There are tons of books, recipes, decorations and family traditions dedicated to his arrival for a successful Holiday season. But how about Data Scientists? Is this new position…|
Added by Vincent Granville on November 29, 2012 at 10:30am — No Comments
Added by Vincent Granville on November 29, 2012 at 8:00am — No Comments
Data Veracity, uncertain or imprecise data, is often overlooked yet may be as important as the 3 V's of Big Data: Volume, Velocity and…Continue
Added by Michael Walker on November 28, 2012 at 3:00pm — No Comments
Added by Vincent Granville on November 28, 2012 at 10:30am — No Comments
Added by Sandeep Raut on November 24, 2012 at 6:12pm — No Comments
Top 50 data science / big data tools, described in less than 40 words, for decision makers. Please help us: any definition that you fill will have your name attached to it: send your definition or new term and definition to [email protected]ping.com.…Continue
October 22, 2012
As some of you may know, StatSoft has launched a program to offer free Enterprise Business Analytics software to aid struggling companies in Greece, Portugal, and Spain with the intent to…Continue
Added by Vincent Granville on November 18, 2012 at 5:00pm — No Comments
Here we go. Enjoy!Continue
Added by Vincent Granville on November 17, 2012 at 2:30pm — No Comments
Transforming into a data-driven organization - turning information into actionable insights is a three (3 ) part strategy:
• Technology – build a modern BI/DW architecture & analytics ecosystem with…
Added by Michael Walker on November 14, 2012 at 9:22am — No Comments
Big Data holds a big promise. But has that promise paid out already? Or are you heading for Big Dollar Disaster? Many take inventory of their data and find out they have terabytes of data lying around. Surely something should be done with that, so here’s how we see a lot of companies going about implementing ‘something’ for their Big Data.
Added by Jos Verwoerd on November 13, 2012 at 2:08am — No Comments
How to use s3 (s3 native) as input / output for hadoop MapReduce job. In this tutorial we will first try to understand what is s3, difference between s3 and s3n and how to set s3n as Input and output for hadoop map reduce job. Configuring s3n as I/O may be useful for local map reduce jobs (ie MR run on local cluster), But It has significant importance when we run elastic map reduce job (ie when we run job on cloud). When we run job on cloud we need to specify storage location for input as…Continue
Added by Rahul Patodi on November 11, 2012 at 8:00am — No Comments
When creating a predictive model, data miners need to “tune” it to make the right kind of mistakes. Setting the cut-off point between ‘promising’ and ‘unpromising’ depends a lot on our client’s biggest concern -- missed opportunities or false alarms.
Data Mining Misconceptions #1: The 50/50 Problem…Continue
Added by Vincent Granville on November 8, 2012 at 1:49pm — No Comments
Predicting election results in the 50 states is actually much more easy than most people think. West Coast and East Coast are democrat, Midwest, Texas etc. are mostly republican (the Midwest becoming more republican because the population is aging due to brain drain by young, smart people - mostly democrats). So indeed the task is not about correctly predicting results for the 50 states, but simply predicting…Continue
Added by Vincent Granville on November 8, 2012 at 11:00am — No Comments
There is little time, about 3 or 4 years, if you wanted to process a large amount of textual data or web logs, you need to mobilize large servers and implement consistent SQL programs, long to be developed long and long to give results. Fortunately requests were few and generally volumes were measured at most in terabytes. Now e-commerce and social media have been largely developed, and many companies see their customer relationships, and therefore their survival, entirely dependent on the…Continue
Added by Michel Bruley on November 8, 2012 at 3:58am — No Comments
Hadoop (MapReduce where code is turned into map and reduce jobs, and Hadoop runs the jobs) is the most well known technology used for "Big Data" because it allows an organization to store huge quantities of data at very low…Continue
Added by Michael Walker on November 7, 2012 at 3:57pm — No Comments