The analytics software category is 30 years old and about $15 billion in size. So why is it that information technology research and advisory firm Gartner has not published a standalone Magic Quadrant on the sector until this year? The answer: Gartner has meshed business intelligence with analytics for the past decade, and viewed them […]
“A Big Workflow approach to big data not only delivers business intelligence more rapidly, accurately and cost effectively, but also provides a distinct competitive advantage. We are confident that Big Workflow will enable enterprises across all industries to leverage big data that inspires game-changing, data-driven decisions.”
I’ve been monitoring a curious and lively discussion over on LinkedIn – “Is it necessary to have a Masters Degree to become a data scientist?” The comments I’ve seen have exhibited a number of points of view on the matter that I think are reflective of the questions on many people’s minds – both those wanting to become a data scientist and those wanting to hire a data scientist.
I am convinced we’re at an important inflection point in the timeline of the discipline of computer science. When compared to other disciplines like mathematics, physics and biology, computer science is a very young field, starting around 1964. But something is happening now, in 2014, that is propelling the field into a new evolutionary period.
A recent big data report was based on a Forbes Insights survey and conducted in association with Rocket Fuel, a provider of artificial intelligence advertising solutions. The report provides insight into how marketers perceive the value of using big data technology to drive marketing initiatives.