James Kobielus
Big Data Evangelist, IBM

As IBM's big data evangelist, James Kobielus is IBM Senior Program Director, Product Marketing, Big Data Analytics solutions. He is an industry veteran, a popular speaker and social media participant and a thought leader in big data, Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management and next best action technologies.

Fogs, logs and cogs: The newer, bigger shape of big data in the Internet of Things

February 26, 2015 | by James Kobielus, Big Data Evangelist, IBM
Big data is becoming the next best thing to true magic. It is everywhere and, increasingly, nowhere specific. Every node in the known computing universe is becoming a component in a vast, distributed, pervasive big data cloud. In an Internet of Things (IoT)-centric world, cloud’s processing,...

The dev@ was in the details, and in my delivery

February 12, 2015 | by James Kobielus, Big Data Evangelist, IBM
Let's take a closer look at the strengths, but mostly the weaknesses, of my Ignite dev@Insight 2014 presentation, “Data science is not a magic wand for diagnosing global warming.”

Spooky action at a personal distance

February 5, 2015 | by James Kobielus, Big Data Evangelist, IBM
Big data analytics is getting positively spooky in its ability to infer our intentions in real-time and in the context of our environments. In the Internet of Things (IoT) era, voice inputs, gestural interfaces, and data-driven inferences will be able to drive remote actions in your personal domain...

Data scientists need to nip model overfit in the bud

January 29, 2015 | by James Kobielus, Big Data Evangelist, IBM
Overfitting is an unfortunate consequence of top notch data scientists attempting to refine their statistical models. It stems from the tendency to skew data science models by starting with a biased set of project assumptions that drive selection of the wrong variables, the wrong data, the wrong...

Simulating customer cognition with or without neuroscience

January 23, 2015 | by James Kobielus, Big Data Evangelist, IBM
Functional simulation, not literal cloning, is the heart of cognitive computing. To understand the cognition of customers or any other human, you should be modeling the higher cognitive, affective and sensory faculties of the mind, not the actual physical components of the brain. Most cognitive-...

Why you may never need to become a data scientist

January 15, 2015 | by James Kobielus, Big Data Evangelist, IBM
The democratization of data science is the best thing that has ever happened to this discipline. However, many users may never need to upgrade their skills to the level of a professional data scientist. What you truly need is the ability to tap into continuous, proactive and authoritative insights...

Fathoming photos at algorithmic speed

January 9, 2015 | by James Kobielus, Big Data Evangelist, IBM
In this era of big media, more and more digital photos are, by default, being uploaded to the cloud soon after they’re captured. But who has the time and, considering the swelling magnitudes of video and photo contents in the world, where would we ever find enough humans to review, curate and...

Patting down the pachyderm: Big data prognostications for 2015

December 23, 2014 | by James Kobielus, Big Data Evangelist, IBM
As 2014 draws to a close, the proverbial elephant that we call big data is smarter, more sensitive and more agile than ever. It’s got a much more varied array of advanced analytics riding on its broad back. More than that, it’s performing these amazing feats as a team player within a growing troop...

Machine learning molds the material world

December 18, 2014 | by James Kobielus, Big Data Evangelist, IBM
Computational modeling has revolutionized all branches of the physical sciences, engineering and design. Leading-edge work in these fields is pushing new computational frontiers at nano scales. Computation-centric methods allow researchers to model, simulate and assess a much wider array of options...

Big data and the power of positive curation

December 11, 2014 | by James Kobielus, Big Data Evangelist, IBM
Curation addresses a purpose that stewardship never has in the data analytic governance context. Whereas stewardship refers to data’s trustworthiness, curation addresses the quality criterion of relevance. Consequently, curators might be regarded as being responsible for a “single version of what’s...