Blogs

Tom Deutsch
Program Director, IBM

Tom Deutsch serves as a Program Director on IBM’s big data team. He played a formative role in the transition of Hadoop-based technology from IBM Research to IBM Software Group, and he continues to be involved with IBM Research big data activities and transition from Research to commercial products. Tom created the IBM BigInsights Hadoop-based product, and has spent several years helping customers with Apache Hadoop, BigInsights and Streams technologies, identifying architecture fit, developing business strategies and managing early stage projects across more than 200 customer engagements. He also co-authored the popular book “Understanding Big Data,” as well as many other papers.

Mapping change to opportunity: New imperatives for big data and analytics

March 26, 2014
A recently released infographic aids in understanding how big data capabilities map back to enterprise strategic imperatives. I'll break this infographics down into steps and discuss each level for clarity and definition. Read More

Why Static STILL Stinks

September 27, 2012
As promised, we’re going to revisit a topic I introduced awhile ago in "Why Static Stinks". Based on what I’m seeing recently, static still stinks, so now is a good time to resurface our discussion. Read More

Selecting your first big data project

July 30, 2012
In this blog, we will cover how to select, staff and plan your first big data project. Our recommendations are based on many years of experience that we have had working with a wide variety of customers in several industries. We won’t focus on specific technologies. Instead, we will examine the organizational dynamics and lessons learned from how these projects go in real life, inside existing, often very busy IT infrastructures. Read More

Social Media Analytics, ROI and Other Non Sequiturs

July 30, 2012
Okay, I’ve bitten my tongue for as long as possible, and I need to get this off my chest. Most, and by most I mean at least 85% of the social media big data initiatives I see are ultimately going to under-deliver their expected ROI or eventually be discarded as not useful enough. Read More