Blogs

Next-generation data science: Open analytics ecosystems

Next-generation data science: Open analytics ecosystems

September 19, 2016 | by James Kobielus, Big Data Evangelist, IBM
Open data science initiatives can be a revolutionary force for innovation that spans diverse industries. And that force comes from the people in different roles and with various skill sets who use open source data science tools to develop and deploy new designs for working and living. Discover why...
A developer's take: Using Hadoop in the cloud to fail fast

Using Hadoop in the cloud to fail fast

September 15, 2016 | by Andrea Braida, Portfolio Marketing Manager, IBM
Chris Snow, a data and application architect, enjoys helping customers with their data architectures and is working extensively on an open source app project in his spare time. Hear what Snow has to say about his IT experience spanning several industries, his current efforts with customers and his...

Streaming analytics goes mainstream

The key to deriving value from the Internet of Things

September 13, 2016 | by Preetam Kumar, Product Marketing Manager, IBM Analytics, IBM
The evolving Internet of Things is fueling a rise in the adoption of streaming analytics across a growing number of industries. Learn more about the rising adoption of real-time streaming analytics in industries and top use cases cited in the recent “Bloor Market Report on Streaming Analytics 2016...
The strong adoption of streaming analytics

The strong adoption of streaming analytics

September 12, 2016 | by Preetam Kumar, Product Marketing Manager, IBM Analytics, IBM
The transformation of the streaming analytics market demonstrates how business process automation is being driven by innovative open source projects and an ever-increasing world of sensor-derived data. See how IBM fared among 14 commercial providers of streaming analytics in a recent Bloor Market...
Next-generation data science: Acceleration for team productivity

Next-generation data science: Acceleration for team productivity

September 12, 2016 | by James Kobielus, Big Data Evangelist, IBM
The productivity of data science teams—often challenged by access and formatting minutiae—can be enhanced by automating many of the manual tasks these teams need to process. Take a peek inside the mind of a data scientist, and see how acceleration of the data science development pipeline can boost...
Collaborate to foster cognitive disruption

Collaborate to foster cognitive disruption

September 9, 2016 | by James Kobielus, Big Data Evangelist, IBM
The importance of data science expertise, techniques and tools in a world rapidly employing advanced cognitive systems cannot be understated. Learn more about how business analysts, data scientists, data engineers, application developers and other professionals with analytical skills sets are using...
5 reasons data scientists are attending World of Watson

5 reasons data scientists are attending World of Watson

September 8, 2016 | by James Kobielus, Big Data Evangelist, IBM
As a working data scientist, you must deliver on your projects while at the same time staying up to speed on changes in your chosen field. That’s a tough balance, considering how stretched you already on the job and how quickly the world of data science is evolving. That’s where IBM World of Watson...
Getting the right mix of analytics specialists in data science teams

Getting the right mix of analytics specialists in data science teams

September 6, 2016 | by James Kobielus, Big Data Evangelist, IBM
The success of next-generation data science initiatives depends heavily on teamwork from the right mix of application developers, business analysts, data engineers, statistical modelers and other specialists. Discover more about the composition of high-quality data science collaboration through the...
IBM Big Replicate: Complete resilience through active-active replication

IBM Big Replicate: Complete resilience through active-active replication

August 22, 2016 | by Andrea Braida, Portfolio Marketing Manager, IBM
And they said resilience—continuous data access in the face of outages, failures and downtime—across distributed data sources is impossible. Yet the recent IBM BigInsights release offers this capability in its IBM Big Replicate technology. Get an inside look at resilience in an interview with Jim...
A sneak peek at the future of data migration: The DNA of Bluemix Lift

A sneak peek at the future of data migration: The DNA of Bluemix Lift

August 8, 2016 | by Ben Landrum, Design Manager, IBM
What does dedication to the client experience look like? To create IBM Bluemix Lift, it meant driving from concept to app in 90 days flat.

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