4D Analytics Framework Combines Customer Analytics with Geospatial, Operational, Temporal and Time-series Data
Written by George Leopold. Originally published in Datanami.com
Teradata Corp. released a “4D analytics” capability that melds three-dimensional geospatial location data with time-series data for edge computing applications.
The cloud-based data and analytics vendor (NYSE: TDC) that has been moving steadily up the technology stack with its platform strategy said its 4D analytics framework combines customer analytics with geospatial, operational, temporal and time-series data. The capabilities are focused on Internet of Things and other edge computing applications that process variable time and location data.
The goal is to help users “operationalize enhanced IoT analytics use cases,” the company said on Monday (April 9).
Teradata is positioning the 4D analytics capability at use cases such as churning through IoT sensor data generated by vehicle fleets, including routes and travel times, to optimize operations and schedule fleet maintenance. Another transportation application addresses traffic pattern analytics ranging from trains to pedestrians as part of a push into the smart cities sector.
In March, Teradata announced a smart cities partnership with Cisco Systems (NASDAQ: CSCO) that combines the networking giant’s IoT and smart cities initiatives with Teradata’s analytics platform. Teradata said it would provide data management tools for Cisco’s smart cities push, which includes aggregating information to improve the efficiency of “siloed” municipal services like traffic, lighting and parking.
Separately, Teradata is promoting a transportation service that combines time-series and geospatial data with demographic and weather information that could be relayed to devices in near real-time, the company said.
The addition of the 4D capabilities to its flagship analytics platform accelerates Teradata’s move up the technology stack via its cloud-based framework as it addresses “IoT analytics.” The approach combines a series of data points gathered at specified intervals to reveal changes over time along with location data gathered by far-flung sensor networks. The result, the company said, is “contextual analytics based on when and where.”
“We are on the brink of a massive explosion of IoT applications and use cases powered by advanced analytics,” said Tim Henry, a Teradata senior vice president. “Devices at the edge, like connected cars, fleets, planes, traffic lights, roads, wearables and so much more, will become smarter and more valuable as new analytic insight is pushed out to them.”
To access the original article, visit Teradata Takes '4D Analytics' to the Edge
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