Blogs

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.

Next-generation data scientist: Harnessing an integrated development environment

Next-generation data scientist: Harnessing an integrated development environment

August 1, 2016 | by James Kobielus, Big Data Evangelist, IBM
A day in the life of data science professionals likely involves navigating the challenges and complexities of sourcing, preparing, modeling, developing and governing data, analytics tools and other assets in collaborative environments. Get a glimpse of the roles that compose data science teams and...
How can data scientists collaborate to build business applications?

How can data scientists collaborate to build better business applications?

June 10, 2016 | by James Kobielus, Big Data Evangelist, IBM
We asked five social influencers how data scientists can collaborate to build better business applications. See what they had to say.
Highlights from the Apache Spark Maker Community Event

Highlights from the Apache Spark Maker Community Event

June 8, 2016 | by James Kobielus, Big Data Evangelist, IBM
Stay on the cutting edge with these highlights from the Apache Spark Maker Community Event as you sit in on interviews with industry leaders and explore the power of the IBM Data Science Experience.
Experiencing deeper productivity in open data science

Experiencing deeper productivity in open data science

June 7, 2016 | by James Kobielus, Big Data Evangelist, IBM
Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building...
Innovative business applications: The disruptive potential of open data science

Innovative business applications: The disruptive potential of open data science

June 1, 2016 | by James Kobielus, Big Data Evangelist, IBM
A world that grows increasingly complex calls for disruptive innovation in an open, collaborative environment. See how open data science provides an ecosystem of expertise, skill sets and advanced open source data science tools that fuels collaborative creativity in the development and deployment...
Boosting the productivity of the next-generation data scientist

Boosting the productivity of the next-generation data scientist

May 24, 2016 | by James Kobielus, Big Data Evangelist, IBM
Use open-source tools to supercharge the data science lifecycle, giving data science teams a boost as they work to provide compelling results in the complex team environments that mark modern corporations. Learn how you can make open data science an ongoing part of your business environment when...
It takes a team: Collaboration and workflow in open data science

It takes a team: Collaboration and workflow in open data science

May 19, 2016 | by James Kobielus, Big Data Evangelist, IBM
Data science takes collaborate teams of data scientists engaging in productive, open data development initiatives that can ensure strong workflow, governance, security and management. See why open environments are revolutionizing the data science landscape.
Spark and R: The deepening open analytics stack

Spark and R: The deepening open analytics stack

May 19, 2016 | by James Kobielus, Big Data Evangelist, IBM
As Spark continues to mature into mainstream adoption in the data science community, the open data analytics stack and open source tools grow more robust, giving data scientists rich core workbenches to develop evermore innovative applications.
Bridging NoSQL databases into open data science initiatives

Bridging NoSQL databases into open data science initiatives

May 10, 2016 | by James Kobielus, Big Data Evangelist, IBM
As a foundation for data lakes and refineries, NoSQL databases provide access, processing and storage to structured and unstructured data for high-performance statistical modeling and exploration. Take a look at the multitude of advantages of NoSQL databases and opportunities to bridge them to open...
Bridging Spark analytics to cloud data services

Bridging Spark analytics to cloud data services

April 21, 2016 | by James Kobielus, Big Data Evangelist, IBM
Apache Spark not only excels at data warehousing, in-memory environments for building data marts and other functions, it also is well suited for pulling data from a wide range of sources and transforming and cleansing that data in an Apache Hadoop cluster. And then there is Spark’s complementary...

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