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June 09, 2017
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TMW: From Adoption to Profitability

The San Jose DataWorks Summit is this Tuesday! Have you registered?

A few weeks ago, we announced Tim Leonard of TMW Systems would be presenting a Tuesday keynote, Commoditizing Your Data to Sell – A Transportation Example. Lessons from this keynote are vital to any small business looking to compete with major players in an industry.

Tim is also one of our Data Hero Finalists in the Data Visionary category. That’s because TMW’s use case is an exceptional one. The company is the leading Big Data transportation technology provider and uses Hortonworks to develop Business Intelligence and Big Data tools that offer valuable business insights to transportation application users. Through Hortonworks, TMW has reduced operating costs, grew revenue by 31%, and greatly expanded its business.

While Tim’s impactful, mainstage keynote will be brief, he’s also hosting a longer Thursday breakout session at 11:30am. Join Tim on as he presents:

How Market Intelligence from Hadoop on Azure Shows Trucking Companies a Clear Road to Profitability

Abstract: TMW Systems (a Trimble Company) has been in the business of long-haul trucking, logistics operations and fleet management for more than thirty years, but we wanted more data, so we turned to our customer community. Now, we turn that data into market intelligence, which we then provide back to our customers. To do this, we invested heavily in Hortonworks Data Platform running on Microsoft Azure in the cloud. In our talk, we’ll share our strategy for capturing operational, maintenance, financial and mobile communications information and how we provide that back to our customer base.

Our approach enables advanced analytics by leveraging Big Data technologies to find new relationships in data that may have been previously overlooked. Survey responses capture business performance metrics, strategy and emerging trends from 150 businesses, representing more than 31 billion dollars in freight movement. Learn how we combine that survey data with other sources like machine and sensor data to help guide our customers to profitability.

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