Thoughts on the Data Ecosystem

The Push and Pull of Enterprise Data Collaboration

Like Doctor Dolittle’s famed pushmi-pullyu, enterprise data projects have a serious agility problem.

Let a Thousand Data Silos Bloom

It’s a story as old as time. It’s a story of evolution, a story of freedom. And it’s a story of stuffing a genie back into its bottle.

Yes, I speak of the ancient enterprise battle royale: Productivity vs. Control.

These battles are constantly happening throughout the enterprise, usually with very good intentions. But, like so many good intentions, they often pave the road to, um… employee circumvention. Hey, gotta get stuff done, right?!?

5 Steps to Faster Data Projects

Data projects come in many shapes and sizes. From big data predictive analytics to small data spreadsheet projects, from building new open data applications to reconciling a couple of ERP tables in the accounting department.

Of Unicorns and Clydesdales: Data Science at the Departmental Level

Much electronic ink has been spilled on the rise of the data scientist.

They’ve been called sexy. They’ve been called unicorns. And, we clearly see a direct correlation between this recent adulation and the uptick in searches for “sexy unicorn”. (At least, I hope that’s the reason).

Decentralized Data Projects are the Norm

In an excellent post, CIO Isaac Sacolick asks, what technologies work best for decentralized data scientists?

Enterprise Data Projects: It Takes a Village

I recently found an article discussing the four different types of Data Scientists. Turns out there’s a quite a bit of wiggle in what the term “Data Scientist” might mean – from business savant to data viz wiz to world class coder to Ph.D. in statistics. A question is posed: