Using Big data alongside OLTP and data warehouses for real time fleet management
Update: 2012-03-15
Description
US Xpress has implemented a single data analytics user interface that pools in information from multiple sources. The logists firm collects 900 data elements from tens of thousands of trucking systems— sensor data for tyre and petrol usage, engine operation, geospatial data for fleet tracking, as well as driver feedback from social media sites.
All of this data is stream both in real time and collected for historical analysis. Information fed to appropriate online transaction processing systems, Hadoop and data warehouses,
In this podcast, Tim Leonard, CTO and vice president at US Xpress, explains how the company processes and analyses Big Data to optimise fleet usage, reduce idle time and fuel consumption and save millions a year as a result.
All of this data is stream both in real time and collected for historical analysis. Information fed to appropriate online transaction processing systems, Hadoop and data warehouses,
In this podcast, Tim Leonard, CTO and vice president at US Xpress, explains how the company processes and analyses Big Data to optimise fleet usage, reduce idle time and fuel consumption and save millions a year as a result.
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