“We are seeing dramatically different models of people attacking the [big data] marketplace and I think it’s healthy… we are also seeing a lot of food-fights going on…that says to me, we’re starting to make money at this, there are real deals going on because people are starting to throw punches”–Dave Vellante, Wikibon.org

“By 2015, 4.4 million IT jobs globally will be created to support big data, generating 1.9 million IT jobs in the United States. In addition, every big data-related role in the U.S. will create employment for three people outside of IT, so over the next four years a total of 6 million jobs in the U.S. will be generated by the information economy. But there is a challenge. There is not enough talent in the industry. Our public and private education systems are failing us. Therefore, only one-third of the IT jobs will be filled. Data experts will be a scarce, valuable commodity”–Gartner

[At eBay] “we tried to address a shocking fact that something like 20% of search queries on the site yielded zero results… the solution was surprisingly low-tech and small-data.  Rather than develop some sort of crazy algorithm to analyze our monstrous volume of data, we instead manually looked at a small set of buying sessions that yielded zero results… It turns out that in this case, a small dataset was sufficient to identify the top 5 problems with our finding experience.  It also turns out that a human being was way more efficient as determining our rate of ‘false negatives’ than a machine”–Rob Go

[Fundraising organization CRUK] “analysed their data and extracted hypotheses to profile their supporters. They wanted to know what made them give…. CRUK then changed their email messaging to make it personalised for these groups. Depending on the segment, people would see different emails, customised with content, layout and images that spoke to their motivations. The results? The email open rate went from 46% to 49%. No story there. But the click through rate went from 21% to 82% (!). Volunteering results increased 300%. This was only possible because of the insights gained from analysis of their data”–Jeremy Davis

“Depending on whom you ask, ‘big data’ is either:

A. Bullshit (Brad Feld)

B. No substitute for judgment (David Friend)

C. The marriage of corporate data with external data (Chris Lynch)

D. Data that’s growing faster than Moore’s law (Richard Dale).

After this week, my answer would be E, all of the above.”–Gregory T. Huang, Xconomy