Recently, I’ve been feeling like I’ve stepped through a looking glass to another similar-but-very-different world. I’m steeped in 20+ years in corporate data warehousing and business intelligence practice. Throughout that time, there have been big and small technology improvements, but nothing truly disruptive (although new…Continue
Added by Stan Mason on April 13, 2012 at 8:30am — No Comments
Added by Patricia Tenanty on April 13, 2012 at 7:30am — No Comments
Outside the traditional business analytics / BI fields.
Added by Vincent Granville on April 12, 2012 at 9:42am — No Comments
“Firestorm” Supercomputer to Help Maximize Turbine Performance
IBM big data analytics software and powerful IBM systems to improve wind turbine placement for optimal energy output. Turbine placement is a major challenge for the renewable energy industry, and Vestas expects to accelerate the adoption of wind energy internationally and expand its business into new markets by overcoming this challenge.
Read more here: …Continue
Added by Stan Mason on April 10, 2012 at 12:30pm — No Comments
There is a great blog post at Sigmod by Joe Hellerstein about MADlib:
MADlib is an open-source library of scalable in-database algorithms for machine learning, statistics and other analytic tasks. MADlib is supported with people-power from Greenplum; researchers at Berkeley, Florida and Wisconsin are also contributing. The project recently released a …
Added by Richard Snee on April 9, 2012 at 9:27am — No Comments
So the question is…when do you sample and when do you not? And does it even matter anymore in the world of big data?
As I’ll lay out here, in most cases today there is no point in wasting energy worrying about it. As long as a few basic criteria are met, do whatever you prefer.
First, let’s take care of the cases where sampling just won’t work. If you need to find the top 100 spending customers, you can’t do that with a sample. You’ll have to look at…Continue
Faces of Deloitte Analytics
eBay, IHG, Equifax and IBM discuss enterprise big data (June 27-28, San Francisco)…
Added by Vincent Granville on April 5, 2012 at 6:29pm — No Comments
Added by Stan Mason on April 4, 2012 at 2:27pm — No Comments
There’s a massive telescope on the drawing board that hasn’t even started construction yet, but when it’s finished in 2024,
it’ll generate more data in a single day than the entire Internet. For scientists to ensure they’ll be able to handle all that raw information, they need to start working on new computing technologies now. Fortunately, IBM is on it.
The computing giant is collaborating with ASTRON (the Netherlands Institute of Radio Astronomy) to develop…
I like to think of the BA role as a broker of information, getting big picture and details from many different people, groups, executives, subject matter experts,…Continue
Added by Vincent Granville on March 30, 2012 at 7:58am — No Comments
Big data must really be big to get its own White House-sanctioned research and development push.
The White House Office of Science and Technology Policy will host a live webcastThursday at 2 p.m. eastern time to outline how the government can “help big data” with its Big Data Research and Development…Continue
Added by Vincent Granville on March 30, 2012 at 6:58am — No Comments
Your firm is awash in workforce data and your team of data scientists have been charged with making sense of it and extracting meaningful insights the business can use. How do you do this? There are many different approaches to analyzing workforce data to choose from but the amount of relevant insight yielded really depends on the goals of the analysis.
If the goal is to take more of a traditional approach to workforce analytics, where the same datasets are massaged to try to squeeze…Continue
Added by Mike Kennedy on March 29, 2012 at 9:18am — No Comments
Read the entire post …Continue
Added by Richard Snee on March 26, 2012 at 1:33pm — No Comments
From MIT's Technology Review -
"Data science is so new that there are no textbooks on the subject, and no university curricula designed to turn out data scientists. Yet it's integral to everything from quantitative trading on Wall Street to ad targeting on the web and the optimization of real-world supply chains."
Social Meets Big Data Webcast - Greenplum Product Announcement
How Social, Open, and Agile is your Big Data?
Join experts from EMC and Greenplum for the announcement of new Big Data technologies, partnerships, and initiatives that will drive greater business insight and economic value from your data than ever before. You'll see for yourself how social web, open-source…Continue
Added by Vincent Granville on March 13, 2012 at 3:32pm — No Comments
Added by Vincent Granville on March 9, 2012 at 3:06pm — No Comments
For statistical process control, a number of single charts that jointly monitor both process mean and variability recently have been developed. For quality control-related hypothesis testing, however, there has been little analogous development of joint mean-variance tests: only one two-sample statistic that is not computationally intensive has been designed specifically for the one-sided test of Ho: Mean2<=Mean1 and StDev2<=StDev1 vs. Ha: Mean2>Mean1 OR StDev2>StDev1 (see…Continue
Added by J.D. Opdyke on March 9, 2012 at 5:42am — No Comments
Added by Vincent Granville on March 5, 2012 at 6:42pm — No Comments
Added by Vincent Granville on March 4, 2012 at 3:09am — No Comments