Open source is a disruptor that never quits, and it is seemingly penetrating and transforming every aspect of established data, analytics and application ecosystems. Give this podcast, recorded at IBM InterConnect 2016, a listen to learn how open source initiatives are transforming machine learning.
Open source is a disruptor that never quits. It seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to David Taieb, a cloud data services developer advocate at IBM, share his
In a podcast recorded at IBM InterConnect 2016, Roger Strukhoff, executive director, Tau Institute for Global ICT Research, shares his expert perspective on how open source initiatives are transforming the Internet Of Things.
As telecommunications companies offer a wider range of services, the amount of data they must process is increasing exponentially. This podcast discusses how telcos can use Apache Hadoop to keep up with rapid data growth.
Bernard Marr, one of the world’s top experts in big data and analytics strategy, made a return visit to our podcast to explain his vision of "SMART big data, analytics and metrics."
You may be surprised to learn that he doesn't really like "big data." In fact, he says "the challenge is to build the
The relational database world has decades of research and experience optimizing SQL access and providing the needed capabilities for mission critical environments. Now, new SQL-on-Hadoop offerings are popping up, which is helping IT departments leverage their existing expertise to move into the big
Big Data without analytics is just data, but how do you perform the analytics? Christy Maver, product marketing manager for InfoSphere BigInsights, answers that question and gives examples of how in-Hadoop analytics are changing the game.
For more information about the IBM big data platform and
Gregory Piatetsky-Shapiro, the editor and publisher of KDnuggets.com, and a well-known expert in business analytics, data mining and data science, joined David Pittman to talk about that mix and the elusive “data scientist unicorn.”
What's in store for big data, analytics and data science in 2014? Big data evangelist James Kobielus walks us through what he sees shaping up in those areas, plus cognitive computing, machine learning, Hadoop, NoSQL and more.
Listen here or read the blog post that spurred this podcast.
Conversations around big data are shifting from "what is big data?" to "what can I do with big data?" Five key use cases have emerged that hold high potential value for many organizations. Eric Sall, vice president of product marketing at IBM, describes those high-value uses for big data. For
With so many conversations about big data, it is inevitable that there will be some mis-information and misunderstandings, some of which take on mythical proportions. James Kobielus, IBM big data evangelist, sets the record straight.