It's time to invite data scientists to the board room

February 20, 2015 | by Beth Smith, GM, Analytic Platform, IBM
The key to uncovering deeper insights is the ability to include more people, with varying diverse backgrounds, to work with data the way they want to.

How everyone can become a data scientist

February 20, 2015 | by Rob Thomas, Vice President, Product Development, Analytics, IBM
IBM announces a set of tools, technology and processes to bring data science to the masses.

5 reasons I love big data and analytics

February 13, 2015 | by Lillian Pierson, Data Viz Wiz, Data-mania
While I’m sure you’ll be off doing something terribly exciting and romantic to celebrate the day of love, a data nerd like me can’t think of anything more captivating than writing about my big love for big data and analytics. As my valentine to you, here are the top five reasons that I love big...

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.”

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...

Extending the power of R to everyone

January 26, 2015 | by Mikhail Lakirovich, Product Marketing Manager, IBM
Learn how Predictive Extensions for IBM SPSS Modeler enables users to leverage the power of R with a simple download and connection to their SPSS Modeler stream.

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...