Jim Scott

Jim Scott - Director of Enterprise Strategy and Architecture, MapR

Jim Scott has held positions running Operations, Engineering, Architecture and QA teams. He is the cofounder of the Chicago Hadoop Users Group (CHUG), where he has coordinated the Chicago Hadoop community for the past 5 years.  Scott has worked in the Consumer Packaged Goods, Digital Advertising, Digital Mapping, Chemical and Pharmaceutical industries. He has built systems that handle more than 50 billion transactions per day, and his work with high-throughput computing at Dow Chemical was a precursor to more standardized big data concepts like Hadoop.

Articles by Jim Scott

In a world where new technologies are often presented to the industry as rainbows and unicorns, there is always someone in a cubicle trying to figure out how to solve business problems and just make these great new technologies work together. The truth is that all of these technologies take time to learn, and it also takes time to identify the problems that can be solved by each of them.

Posted January 05, 2018

Many people are unsure of the differences between deep learning, machine learning, and artificial intelligence. Generally speaking, and with minimal debate, it is reasonably well-accepted that artificial intelligence can most easily be categorized as that which we have not yet figured out how to solve, while machine learning is a practical application with the know-how to solve problems, such as with anomaly detectio

Posted September 20, 2017

When people talk about the next generation of applications or infrastructure, what is often echoed throughout the industry is the cloud. On the application side, the concept of "serverless" is becoming less of a pipe dream and more of a reality. The infrastructure side has already proven that it is possible to deliver the ability to pay for compute on an hourly or more granular basis.

Posted May 15, 2017

It is difficult to find someone not talking about or considering using containers to deploy and manage their enterprise applications. A container just looks like another process running on a system; a dedicated CPU and pre-allocated memory aren't required in order to run a container. The simplicity of building, deploying, and managing containers is among the reasons that containers are growing rapidly in popularity.

Posted April 07, 2017

With all the talk about "big data" in the last few years, the conversation is now turning to: What can be built on this platform? It isn't just about the analytics—many people talk about data lakes, but in reality, organizations are looking beyond the data lake.

Posted February 03, 2017

Choosing when to leverage cloud infrastructure is a topic that should not be taken lightly. There are a few issues that should be considered when debating cloud as part of a business strategy.

Posted October 04, 2016

In the wide world of Hadoop today, there are seven technology areas that have garnered a high level of interest. These key areas prove that Hadoop is not just a big data tool; it is a strong ecosystem in which new projects coming along are assured of exposure and interoperability because of the strength of the environment.

Posted June 03, 2016

NoSQL databases were born out of the need to scale transactional persistence stores more efficiently. In a world where the relational database management system (RDBMS) was king, this was easier said than done.

Posted March 29, 2016

The year 2015 started out with people recognizing that the Hadoop ecosystem is here to stay, and ended as the year in which organizations achieved real success within the Hadoop ecosystem. Today, more projects are popping up within the Hadoop ecosystem that can run both with and without Hadoop. The great thing about this trend is that it lowers the barrier to entry for people to get started with these technologies. More importantly, all of these new technologies work best at large scale within the rest of the Hadoop ecosystem, while Hadoop MapReduce has begun its ride off into the sunset.

Posted January 19, 2016

We live in an "as-it-happens" world, and consumers expect on-demand everything—TV, taxi service, you name it. That same culture is now (and rightly so) expected in businesses. Don't just think about "good enough"—think and plan for real time. The technology is here now to leverage real time in your business for shorter feedback loops, improved time-to-market, and happier customers. The sooner, the better. It's never too early for real time. "Good enough" simply isn't, well, good enough anymore.

Posted October 13, 2015

Google white papers have inspired many great open source projects. What has been missing until now, however, has been a way of bringing these technologies together such that any data-centric organization can benefit from the capabilities of each technology across its entire data center, and in new ways not documented by any single white paper. This is called the "Zeta Architecture."

Posted May 19, 2015

In order to truly appreciate Apache Drill, it is important to understand the history of the projects in this space, as well as the design principles and the goals of its implementation.

Posted April 08, 2015