Featured Author

Jack Norris
SVP, Data & Applications, MapR

Jack drives understanding and adoption of new applications enabled by data convergence. With over 20 years of enterprise software marketing experience, he has demonstrated success from defining new markets for small companies to increasing sales of new products for large public companies. Jack’s broad experience includes launching and establishing analytic, virtualization, and storage companies and leading marketing and business development for an early-stage cloud storage software provider.

Jack has also held senior executive roles with EMC, Rainfinity (now EMC), Brio Technology, SQRIBE, and Bain and Company.

Author's Posts

Posted on January 18, 2017 by Jack Norris

In this week's Whiteboard Walkthrough, Jack Norris, Senior Vice President of Data and Applications at MapR, explains how the MapR Converged Data Platform opens up the use of containers to the big data environment such that you can access data directly, thus taking advantage of otherwise under utilized assets.

Posted on November 9, 2016 by Jack Norris

As I discussed in my presentation at the Gartner Symposium/ITxpo in Florida, digital transformation is a key topic for business leaders today. While the impact of digital transformation is easily understood what is less clear are the steps to effectively pursue a digital transformation -- and the three keys to ensure successful digital transformation.

Posted on October 6, 2016 by Jack Norris

This week I attended my sixth Strata + Hadoop World. Actually, in the beginning they were two separate shows, but the evolution since has been more than the combining, or convergence if you will, of the two shows. The first shows were attended almost exclusively by technologists looking to learn and understand new big data technologies, especially Hadoop.

Posted on April 7, 2016 by Jack Norris

There are substantial advantages to being able to make decisions at the speed required to respond to events in the moment. In fact, real time is at the foundation of many transformational applications. Let’s take a closer look at what real time really means, and why real time is required across the entire process.

Posted on October 12, 2015 by Jack Norris

The cost of waste, fraud and abuse in the healthcare industry is a key contributor to spiraling health care costs in the United States. In 2012, healthcare waste and abuse accounted for nearly $60 billion.

Posted on May 5, 2014 by Jack Norris

I’m on a plane to London as I write this.  As usual, the plane is filled to capacity and coveted snack items are scarce.  The airlines must know something about passenger consumption behavior … or do they?  Accessing multiple pieces of data and analyzing the information in every imaginative way for an actionable result is what is driving Apache Hadoop technology.  MapR is helping companies take advantage of that.

Posted on February 24, 2014 by Jack Norris

The recent O’Reilly Strata Conference held in Santa Clara was high energy, with many attendees focused on discussing details about Hadoop deployments. It has progressed a long way from the early days, when most of the conversations were about “what is Hadoop?” 

Posted on July 27, 2011 by Jack Norris
Check out M.C. Srivas’ Hadoop Summit presentation. Srivas, the CTO and co-founder of MapR, outlines the architectural details behind MapR performance advantages. This technical discussion also describes the scale advantages of the MapR distributed NameNode and provides comparisons to HDFS.
Posted on July 18, 2011 by Jack Norris
A lot of solutions talk about how they handle Big Data, but Hadoop is unique. Hadoop does things that aren’t possible with other solutions -- or if they are possible, they are prohibitively expensive or complex. Hadoop is not an open source alternative to something that’s been on the market for years. That’s why there’s such a premium on key infrastructure innovations like those from MapR.
Posted on August 2, 2011 by Jack Norris
Ted is just back from OSCON where he co-presented Hands On Mahout - Mammoth Scale Machine Learning. The slides are available for this tutorial that covered the evolution of Mahout for clustering and classification of large datasets. If you’re interested in hands-on instruction for machine learning and how specific algorithms can be used to solve real-world problems – this is the session.


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