Posts tagged ‘business intelligence’
By Marilyn Craig, Managing Director, Insight Voices
As you may or may not know, we are in the midst of a 3-part series on data science, covering roles, skills, etc.—generally what you should think about as well as what’s not as important (no matter what the latest articles say!). For Part 2, we have a guest poster—Marilyn Craig of Insight Voices. Marilyn is what I like to call a “classic quant.” She has been at the forefront of big data and data science before most people knew these terms (and spaces) existed and has been my go-to person whenever I had an analytics question (see title) that I needed an answer to. In this post, Marilyn looks at insights and makes the case for why we should all care far more about answers. Take it away Marilyn!
Here’s an interesting question for this new world order of Big Data Analytics: what’s an Insight and what’s an Answer? Sometimes they are the same, sometimes not. An insight is a piece of information or understanding. It may or may not be useful. It may or may not help your business improve, solve world hunger, or even make sense. An answer is always useful. It is the result of asking a question. And the best kinds of answers are those that solve the questions that you really care about. (more…)
In Search of Elusive Big Data Talent: Is Science Big Data’s Biggest Challenge? Or Are We Looking in the Wrong Places? (Part 1 of 3)
When we talk to prospects about their big data initiatives our conversations usually revolve around issues of complexity that goes something like this:
“Big data is so big (no pun intended), there’s such a variety of sources, and it’s coming in so fast. How can we develop and deploy our big data projects when everyone is telling us that we need lots and lots of data scientists and oh, by the way, there aren’t enough?”
Admittedly, many media outlets and pundits are positioning the search for skilled big data resources as what I can only characterize as the battle for the brainiacs. Don’t get me wrong, I am not disputing McKinsey’s report on big data last year that made it clear a talent shortage was looming, estimating that the U.S. would need 140,000 to 190,000 folks with “deep analytical skills” and 1.5 million managers and analysts to “analyze big data and make decisions based on their findings.” But the hype surrounding the data scientist is getting a bit absurd and we seem to be forgetting that those 1.5 million managers and analysts may already be “walking amongst us.” Is a shortage of data scientists really big data’s biggest challenge? (more…)
It’s a legitimate question that we get asked a lot: why can’t I use my multi-billion dollar BI system to manage my big data/real time analytics problem(s)? I have found that my tongue in cheek answer “we need you buy our software and services because we have families to feed” though true, is not as compelling to customers as I would like which leads to today’s post.
To put the question another way: what can PatternBuilders and the rest of the new approaches to data and analytics like Hadoop or Mongo (which, by the way, our platform uses and is a great technology) offer you over and above what large BI company X offers? (more…)
A few years ago, we founded PatternBuilders after noticing that those of us in the software business had won the war and had convinced the entire world that capturing every possible transaction in a digital format and automating all their processes was not only a good idea, but a necessary survival skill. At the same time, however, we almost universally failed in providing ways to do any real analysis on the tons of digital data that were now being captured and available to be used. (more…)