Interesting answers to the question ‘What’s the next big thing after Big data’ at Quora:

Charles H Martin, Consultant, I predict things

The next big thing will be automated machine learning systems that can sift through the big data  sets and discover patterns without deep human intervention.

This will require intelligent systems that can guess feature spaces, kernels, and regularizers, running in parallel on thousands of nodes, with amazing graphical user interfaces and super-easy human computer interfaces.

It would interface with existing data sources, using intelligent hashing / projection operator algorithms to eliminate ETL and other data schema issues.

via stoweboyd.com

Scott Thompson has reorganized the company around three ‘groups’: consumer, regions, and technology. But his long term plan is totally unclear, despite having taken three months to get set. My sense is that he’s moving the deck chairs around on the Titanic, rather than addressing the gaping hole in the side of the boat.

However, trying to centralize the business on capturing user information exhaust does at least line up with what others — Facebook and Google, for example — are planning, so at least he’s looking in the right direction.

[Gerd Leonhard and I spoke in San Francisco last night about big data and its place in the social web, along with Jamais Cascio and Andreas Weigend.]

NESTA put together 12 predictions for 2012, and one was the rise of the new reporter: the data journalist.

Dan James via 12 Predictions For 2012 — NESTA

The task of the data journalist is to filter and interpret these huge datasets to make a compelling story. And this is where it gets interesting, because data journalism gives us a new way to make facts compelling. Traditional investigative journalism has tended to drill down - to unearth hidden truths in current events. By contrast, data journalism often works in the other direction by aggregating small details to create a bigger picture. This role has previously been played by expert inquiries and academic studies, once public interest has died down. But data are increasingly available in (almost) real time, and social media can be used to harness collective intelligence, for example to build up a picture of contextual factors implicated in this summer’s riots. Such ‘emergent truths’ may be less exciting than a killer scoop, but they make up for it in relevance to the reader and local detail. Data journalism can empower readers to break stories down to a hyper-local level, allowing readers to zoom in to their constituency or neighbourhood to find out what would happen under AV system, filtering by personal circumstances, or search for cases of interest.

Nathan Jurgenson coins the term ‘information camouflage’ (in Predictive analytics and information camouflage): companies that mine data about us, discern a pattern they can exploit, and then conceal that knowledge by randomizing the torrent of ads and promotions they send our way so they can conceal that they are on to us, since if we knew we’d change our mental filters.