You are hereHome › Blogs
Big Data Evangelist
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
April 4, 2013
Big data has its discontents. The backlash is a necessary reality-check in an otherwise vibrant arena. Often in this industry, when a technology is vogue, the hype can interfere with rational decision making, both among users and among solution providers.
March 29, 2013
Nothing screams “speed of business” quite like in-memory technology. On Wednesday, March 27, I participated in an IBM Twitter chat with analysts, influencers, thought leaders, fellow IBM-ers and others on this very topic. The event took take place from 12-1pm EDT and used hashtag #bigdatamgmt.
March 28, 2013
Quality-of-service (QoS) is one of the most paradoxical metrics in the telecommunications industry. “Quality” of the customer experience is normally measured through surveys and logged feedback, but plenty of data can lead to good quantitative measures.
March 20, 2013
Smartphones and other mobile gadgets have become integral to every aspect of modern life. So it’s no surprise that enterprises everywhere are starting to tap into them as a rich source of data for deep analysis in Hadoop, NoSQL and other big-data platforms.
March 14, 2013
Big data is not a religion. Rather, it’s an analytics paradigm that enables business outcomes beyond what can normally be achieved at lower volumes, velocities and/or varieties of data.
March 7, 2013
Most of us don’t think of big data as a personal resource for mobility, but, clearly, that thinking will need to change. Smarter mobility depends on the ability to serve all of our mobile devices from an intelligent big-data infrastructure
February 28, 2013
When talking about big data, the terms "structured" and "unstructured" often arise. Data scientists must boldly break out of the structured data world to consider not only unstructured data, but also unstructured processes and governance, and collaboration models in big data applications.
February 21, 2013
Big data can’t prove its business value if it remains in a perpetual proof-of-concept phase. How can you prepare your big-data deployment for delivery into a production IT environment? What exactly does it mean to say that big data, or any IT initiative, is truly production-ready? James Kobielus gives helpful tips.
Controlled Explosion: Keeping Big Data Contained with Security, Governance and Information Lifecycle Management
February 14, 2013
To control the big data explosion, you must keep it contained with a well-balanced strategy that involves security, governance and information lifecycle management controls.