Teradata today introduced two new software services — Teradata Listener and Teradata Aster Analytics on Hadoop — aimed at helping customers operationalize Internet of Things (IoT) data.
"This is about the Internet of Things coming of age," says Chris Twogood, vice president of Product and Services Marketing for Teradata. "When people can start to analyze data at this volume, that's where real value happens."
With the new software capabilities, Teradata aims to eliminate the complexity and latency around ingesting a massive and constant stream of data and then extracting value from it.
Teradata Listener is an intelligent, self-service software built on open source projects like Apache Kafka, that's designed to allow the ingestion of fast-moving streams of sensor and IoT data wherever it exists globally and then propagates the data into multiple platforms in an analytical ecosystem — Hadoop, Spark, IBM Streams, Teradata Aster Analytics, Teradata Database, etc. You can then analyze data from numerous sources, including sensors, telematics, mobile events, click streams, social media feeds and IT server logs without turning to IT for help.
Ready to roll with analytics
Meanwhile, Teradata Aster Analytics on Hadoop provides native integration of Aster Analytics and Hadoop, making it a first-class engine within the Hadoop infrastructure. It's an integrated analytics solution that now features a set of more than 100 business-ready analytics techniques and seven vertical industry applications that run directly on Hadoop.
For instance, Two good points to one Teradata customer, a major manufacturer that sells and services magnetic resonance imaging (MRI), radiography and ultrasound imaging equipment to global hospitals and clinics. Text logs describing patient behavior and sensor data stream from the equipment into the manufacturer's Hadoop data lake on a 24/7 basis.
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