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Ron Powell

Thanks for visiting my blog. As co-founder of the BeyeNETWORK, acquired by TechTarget in 2010, I am privileged to participate in many industry-related activities as a BeyeNETWORK expert covering business intelligence and analytics. These events provide me with a unique insider perspective into the business intelligence ecosystem, its products and the vendors that provide those products. I'll be sharing that invaluable information with you through this blog, which will also be a reflection my business philosophy. And, just to make this interesting, I'll be sure to include my personal point of view on a wide range of topics and share some of the stories of people I meet in my travels.

About the author >

Ron, an independent analyst and consultant, has an extensive technology background in business intelligence, analytics and data warehousing. In 2005, Ron founded the BeyeNETWORK, which was acquired by Tech Target in 2010. Prior to the founding of the BeyeNETWORK, Ron was cofounder, publisher and editorial director of DM Review (now Information Management). Ron also has a wealth of consulting expertise in business intelligence, business management and marketing. He may be contacted by email at rpowell@powellinteractivemedia.com.

More articles and Ron's blog can be found in his BeyeNETWORK expert channel. Be sure to visit today!

We are seeing a major sea change in how enterprises are harnessing big data through machine intelligence and deep learning. Graphical processing units (GPUs) excel at workloads that require large amounts of mathematical calculations, simulations, streaming data and machine learning. This has resulted in a paradigm shift, enabling a whole new range of applications for autonomous vehicles, Industrial Internet of Things (IIOT) and advanced analytics.

I recently interviewed Amit Vij, CEO of Kinetica, whose company has pioneered a database that uses general purpose graphical processing units that is run SIMD operations in a highly parallel fashion. Its GPU-accelerated analytics database provides real-time insights into large and streaming datasets.

Kinetica was incubated within the U. S. Army Intelligence Command and the NSA.
It started as a geospatial and temporal computational engine and slowly evolved to a highly available and distributed in memory database that is accelerated by GPUs.

Kinetica can scale to meet the needs of very computational intensive applications such as risk mitigation and fraud detection in the financial industry. Their technology can displace current technologies that utilize scale-up hardware as Kinetica leverages scale-out architectures.

According to Amit, a major value proposition is converging machine learning and deep learning into a database running in-database analytics, registering, for example, a Google TensorFlow library to Kinetica, running a machine learning model on a data table that has over one billion rows, and then persisting out a new data table. "We're seeing that as an easy workflow for an organization to use," said Amit.

GPUs are accelerating the use of analytics across a broad range of use cases and having a profound impact across a wide variety of industries. Organizations that are trying to achieve real-time analytics with large and streaming datasets should check out Kinetica.

To read my full interview with Amit Vij, click here.

Posted June 20, 2017 7:49 AM
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