How Much “Data Science” Do You Really Need?

Is it really true that “Nearly two-thirds of big data projects will fail to get beyond the pilot and experimentation phase in the next two years, and will end up being abandoned,” as suggested by Steve Ranger last year in Your big data projects will probably fail, and here’s why?  My take: to be successful […]

How Important Is “Perfect Data” To Data Analytics Programs?

Back in 2014 I published a guest post on the Open Data Institute’s web site titled How important is the quality of open data? Here’s a quote from that piece: Setting aside for the moment how we define “quality” … database managers have always had to concern themselves with standards, data cleaning, corrections, and manual […]

The Tip of the Spear II: Connecting Big Data Project Management with Enterprise Data Strategy

“If data analysis is Big Data’s “tip of the spear” when it comes to delivering data-dependent value to customers or clients, we also must address how that spear is shaped, sharpened, aimed, and thrown – and, of course, whether or not it hits its intended target.” Introduction In Meeting the Mission of Transportation Safety, Richard […]

Big Data Project Management: Data Must Flow!

I’m currently researching big data project management in order to better understand what makes big data projects different from other tech related projects. So far I’ve interviewed more than a dozen government, private sector, and academic professionals, all of them experienced in managing data intensive projects. What I’m finding is that professionals with experience managing […]

Big Data Project Management: What’s In & What’s Out?

Here’s something to think about when you’re planning a big data project: are you planning a project or a program? Here’s a simple distinction: A project typically has a beginning, middle, and end. A program is something ongoing and relatively permanent. Projects Relatively self-contained big data projects may be tied to an ongoing process or program […]