Big Data Has Exhaust Problem – InformationWeek

Say no to data obsession and focus on the business problem you want to solve, says Berkeley data science professor.


"A better question is: ‘What do my customers really want and need and desire?’ " Weber tells InformationWeek. "And then: ‘What kind of data would I need to collect, and what would I need to do with it to help them?’ "

Big data analytics firm Zettics grows steadily by selling insights about cell phone usage to major carriers – Boston Business Journal


Fresh off a recent acquisition and executive-level hire, the company, which offers four major analytics products and analyzes 3 trillion records monthly, is eyeing continued international expansion in Western Europe and East Asia, Levy said

Tamr CEO Andy Palmer explains why every business needs to put all its data sources together

Tamr uses advanced machine learning to combine hundreds or even thousands of data sources. It crawls all the available data then makes recommendations on how to blend them.


Palmer tells the story of a customer with 15,000 data sources in desperate need of curation. Another customer needed to combine 300 different billing systems. You probably won’t believe how long it took Tamr’s software to sort those issues out.

Researchers Use Big Data to Get Around Encryption – Digits – WSJ

Companies are racing to encrypt their data to block hackers and government spies. But researchers have found that data mining techniques can get around one widely used version of the technology.


The attack described in a recent research paper, focused on the technology called Hypertext Transfer Protocol Secure, or HTTPS, which is used to identify sites and encrypt traffic over the Internet between users’ devices and remote servers

What’s machine learning? It depends on who you ask

As interest in machine learning has grown, its definition has expanded to include a panoply of techniques for automating knowledge and pattern discovery from fresh data


Increasingly, the term "machine learning" is also beginning to acquire a catch-all status. Or, at the very least, machine learning has become a convenient handle that today’s data scientists use to refer to the wide range of leading-edge techniques for automating knowledge and pattern discovery from fresh data, much of it unstructured. People’s working definitions of machine learning seem to be creeping into broader, vaguer territory.

Unlocking Big Data’s Value Potential Through Design with Small Data

Co-written by Finn Birger Lie

Big Data is perceived as the next value opportunity for corporations to innovate and grow. To be of any real value, however, Big Data has to become more accessible and understandable to non-specialist users and leave …


Most organizations do not have terra or petabytes of useful data available to them. However, the most important aspect of Big Data is not so much the volume of a dataset, but more in the insights derived from combining several, dispersed, smaller datasets. More data means more reliable insights but it does not automatically guarantee more insights.

Making art out of the data of everyday life

For followers of a growing self-discovery movement, the quantities in our lives can say a lot about its quality—and be transformed into art.


People have been tracking personal data for as long as there have been devices to measure it, but quantified self didn’t begin until 2008, when Gary Wolf and Kevin Kelly, two editors at Wiredmagazine, realized that technology was making it easier and cheaper to track personal data. Smartphone apps not only can record your location, how many steps you take each day, or how much you toss and turn when you’re sleeping, they can also export the data into spreadsheets and charts and graphs so you, the user, can make sense of it.

News recap: Survey spotlights top data mining tools

RapidMiner is among the most used data mining tools and executives still dont trust analytic findings in this weeks news recap


In a blog post accompanying the survey results, KDnuggets president Gregory Piatetsky said the results, particularly the low adoption of Hadoop, show that the most advanced big data technologies are mainly being used at a small group of web giants and isn’t likely relevant to smaller organizations. However, as advanced tools become simpler and more affordable, this may change.

Remember, Kids, Stay in school!

Love it! “Basically, my articles, my work, and about 80% of my life as I read somewhere, wouldn’t have been possible without DROPOUTS” But I do not endorse dropping out, I did but it made my life so much harder that it had to be! Stay in SCHOOL!!!!!

Data Scientist: the New Quant – Data Matters


Today, as an industry, we are only scratching the surface of the potential of big data. Data scientists hold the keys to that potential. They are the new statisticians. They are the new quants.