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March 05, 2014

Amdocs TeraScale: A Carrier-grade Big Data Solution for Real-time Usage Data Management and Analytics Enablement

At Mobile World Congress (News - Alert) 2014, Amdocs has pulled the wraps off its Amdocs TeraScale, a carrier-grade, big data solution designed to cost-efficiently store, manage and extract real-time charging usage data for analytical use cases.

Amdocs (News - Alert) TeraScale leverages big data store technologies based on the Hadoop ecosystem, and enables deeper, more rapid real-time analytics through innovative usage data modeling and embedded ETL (extract, transform and load) processes. The new solution includes the Amdocs CES (News - Alert) 9.1 product suite.

Amdocs TeraScaleis designed and tested to deliver the carrier-grade performance, security and availability required in service provider’s operational environments.

Rebecca Prudhomme (News - Alert), vice president of product and solutions marketing at Amdocs, said in a statement, "With Amdocs TeraScale, we are leveraging this knowledge to introduce a solution that not only generates considerable cost-efficiencies for our customers in a core operational area such as data storage.”

The solution is capable of streaming the massive volumes of usage data generated by Amdocs Convergent Charging directly into TeraScale data clusters based on Hadoop.

Justin Ven der Lande, principle analyst for analytic software strategies at Analysys (News - Alert) Mason, stated, “Amdocs TeraScale addresses the challenges facing service providers in the area of usage data today: how to cost-effectively store massive volumes of usage data; and how to unlock the value of usage data via analytics to drive better customer experience and to grow revenues. With this new solution, Amdocs is evolving its customer experience systems portfolio to enable service providers to gain analytical insight they did not have before, based on real-time usage data, which paves the way towards new standards of operation and quality of service.”

Amdocs TeraScale enables service providers to explore and visualize usage data using optimized usage queries and extracts as well as native Hadoop query tools. It can be initially deployed as a side-by-side solution alongside existing usage data storage and ETL solutions, with no impact on charging and billing operations.




Edited by Cassandra Tucker
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