Our newsletter has four sections, separated by horizontal lines: Announcements, Message From The Editor, Best Blogs, and Job Ads.

1. Announcements…

Machine data is the fastest growing, most pervasive part of “big data”. It is also the most valuable, containing a critical record of user behavior, security risks, service levels, fraudulent activity, customer experience and more

Locu

What does it do? Founded in 2010, Locu's mission is to structure the world's information, and it is currently focused on unstructured local data. Locu combines document analysis,  crowdsourcing,  and machine learning to provide structured and semantically annotated data sets made available through a set of APIs. Locu’s first product  helps restaurants better manage their online…

Should you be proactive, hire an expert before a crisis, or just hire someone when you have a major problem, such as

1. Huge, unexpected churn requiring root cause analysis (happened to T-Mobile in 2011)
2. Increasingly sophisticated…

Two new research reports on big data flash out its early impact on enterprise IT.

David Newman, Research VP at Gartner and a member of its Enterprise Architecture team, warns in Big Data Disruptions Tamed With Enterprise Architecture that “Big data will disrupt your business. Your actions will determine whether these disruptions are positive or negative.“ Newman sees three areas…

Sometime today, shares of the data analysis company Splunk will start trading on the Nasdaq National Market in New York, after pricing last night at $17 a share. The company’s offering has raised about $230 million.

Splunk is not your traditional big-data company, in that it is running some variant of Hadoop, like so many upstart companies in that space. Its specialty, as …

Also read the answer to the question "how do I become a data scientist"?

This Analyticbridge interview is part of a blog post series about data scientists , what they do in their daily life, how they found their job, what techniques they use, corporate culture and benefits in their work place, etc. The previous posting was featuring people working for Deloitte Analytics, click here for…

Companies hiring analytic talent have been complaining for a few years about how hard it is to find good data scientist. Our analysis of job board data (based on Indeed, Datashaping and Analyticbridge statistics) reveals that a job ad specifying two possible locations - e.g. San Francisco, CA or Boston, MA - generates on average 5 times more page views, than a job ad targeting a single location.

The impact is…

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…

BIG data, Mobile, Web, Cloud - Plate Tectonics, But Not an Earth Quake for Some -The Destruction/Construction of Trillion Dollars Shift in the Next 10 years

Outside the traditional business analytics / BI fields.

1. Algorithms and Numerical Techniques
2. Application Design and Porting Techniques
3. Astronomy and Astrophysics
4. Audio, Image and Video Processing
5. Bioinformatics…

“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: …

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 …

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…

Faces of Deloitte Analytics

http://www.analyticbridge.com/group/faces-of-analytics-and-data-sci...

eBay, IHG, Equifax and IBM discuss enterprise big data (June 27-28, San Francisco)…

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…