Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Speed, scale, smarts: GPU-powered analytics for the extreme data economy (sponsored by Kinetica)

Michael Mahoney (Kinetica)
2:55pm–3:35pm Wednesday, 09/12/2018
Sponsored
Location: 1A 04/05

What you'll learn

  • Learn how to leverage the power of GPUs to solve complex data challenges

Description

Widespread digital transformation and the explosion of the internet of things has led to a dramatic increase in the volume, complexity, and unpredictability of data. This goes beyond the challenges of big data into a new world of extreme data where data can be structured or unstructured, static or streaming, machine or human, and long-lived or perishable. Traditional analytical database solutions running on CPUs can’t deliver results on extreme data in real time; new solutions are required. As businesses are being disrupted across all industries by new, nimble digital challengers, it’s critical that organizations remain innovative. Those that are able to turn extreme data into insight that powers their business will gain a competitive edge.

Harnessing the massive parallel processing power of GPUs, new engines like Kinetica are helping businesses with the challenges of extreme data. The Kinetica engine converges advanced analytics, geospatial insights, and machine learning on a single platform. This enables both business analysts and data engineers to leverage data to power real-time business insights.

Michael Mahoney demonstrates how to leverage the power of GPUs to converge streaming data analysis, location analysis, and streamlined machine learning with a single engine and shares real-world case studies on how Kinetica is used to solve complex data challenges.

Topics include:

  • How GPU-powered analytical engines are different than traditional databases
  • How the power of GPUs can be leveraged to converge streaming data analysis, location analysis, and streamlined machine learning with a single engine
  • A live demo analyzing streaming data with large historical datasets in many different ways, including running a machine learning model on the data, all in real time
  • Real-world case studies on how Kinetica is used to solve complex data

This session is sponsored by Kinetica.

Photo of Michael Mahoney

Michael Mahoney

Kinetica

Michael Mahoney is the worldwide vice president of solution engineering for Kinetica. He has over 20 years of experience leading and developing highly skilled and professional solution engineering teams. Previously, Michael was the vice president of solution engineers at MapR, transforming the team into an enterprise-oriented organization, and spent 10 years at Oracle in various groups within applications and technology, focusing on driving analytic solutions for their strategic customers. Michael has also held various management and individual contributor positions at Transamerica, Witness Systems, and Cognos. He holds a BS in business specializing in management information systems.