See: http://bit.ly/RWBoCk…

A Big Data decision support system requires particular capabilities in terms of volume, variety of data and processing speed.



Today companies to improve their knowledge models and forecasts, do not hesitate to take into account hundreds of factors, and do not hesitate to bring up new means of analysis that can handle large volumes of data. But the processing of large volumes of data is a challenge for traditional BI infrastructure. Storing large volumes is not a problem, but…

First, let me say how pleased I am to be a part of the Data Science Central community. While I was the VP of Marketing at EMC Greenplum, I had a front row seat to the dynamic and very exciting “Big Data” and “Data Science” shows. EMC Greenplum has played a pivotal role in helping organizations of all sizes start the process of orienting their businesses and decision-making around data. It has been said, and I’ll say it again –the companies that embrace the power of data and live that life…

This year has seen consolidation and engineering around improving the basic storage and data processing engines of NoSQL and Hadoop. That will doubtless continue, as we see the unruly menagerie of the Hadoop universe increasingly packaged into distributions, appliances and on-demand cloud services. Hopefully it won’t be long before that’s dull, yet necessary, infrastructure.

Looking up the stack, there’s already a line up of cool tools for data scientists and not to be left out,…