Here are the quick-hit ponderings that I posted on various LinkedIn big data discussion groups this past week. I opened up one new theme–Big Media (which I'd introduced a few weeks back at this IBM big-data-relevant site) –and extended my existing discussions of peta-governance (going beyond what
James Kobielus recaps last week's quick-hit ponderings, covering meaty metadata, proofs of concept, the role of behavioral analytics in recommendation engines, decision scientists, and the speed of thought.
developerWork's Scott Laningham interviews IBM Big Data Evangelist, James Kobielus, on why big data is so important, the role of Apache Hadoop and IBM BigInsights in making sense of big data, the evolving role of the data scientist, and and where data warehousing and big intelligence fit in.
One of the myths I deflated a few blogs ago was this prevailing notion that, as I expressed then, "data scientists are just an elite bunch of precious eggheads."
Well, maybe I was slightly exaggerating the myth for comic effect, but that statement, in spirit, sums up how traditional business
Smarter business is a game of incremental improvements. It depends on your ability to produce a steady stream of innovations in your operational processes.
Incremental tweaking is not usually a glamorous activity. Minute process adjustments don't usually call attention to themselves. And that's a
Game-changing analytics applications don't spring spontaneously from bare earth. You must plant the seeds through continuing investments in applied data science and, of course, in the big data analytics platforms and tools that bring it all to fruition.
Big data is not just about scaling your data analytics processing platforms to keep up with the onslaught of new information. Just as important, big data is about bringing together your best and brightest minds and giving them the tools they need to interactively and collaboratively explore rich