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Teradata Democratizes Big Data with Aster Connector for Spark


Teradata has introduced the Teradata Aster Connector for Spark, an integration of Apache Spark analytics with Teradata Aster Analytics.The connector enables pre-built analytics functions from both solutions to be executed from Aster Analytics, enabling anyone who can use Aster Analytics to also run advanced analytics on Spark without the need to learn or know Scala.

According to Teradata, the new connector for Spark solves a key problem in that there is a great amount of interest in the in-memory performance and analytical capabilities of Spark, but not nearly enough data professionals with Spark skills and experience with Spark interfaces and coding compared to those with SQL skills.  

Teradata says its new Aster Connector for Spark aims to democratize big data through self-service, business-focused, analytic solutions so that organizations can more quickly identify revenue-driving insights and accelerate business performance.

"The beauty of the Teradata Aster Connector for Spark is its application for a variety of use cases in just about any industry," said Raghu Chakravarthi, vice president of Teradata Aster Engineering.

For example, he said, could be used as the repository for customer data and finance data, and once Aster pre-processes these, machine learning from Spark could be applied to create automatic credit ratings for each customer, and analysts could then use the credit ratings as a variable in a predictive model that ascertains the likelihood of certain outcomes, such as the customer purchasing a new automobile in the next 12 months.

Another use case arena for the Teradata Aster Connector for Spark is in the IoT arena, where large volumes of sensor data are ingested and pre-processed using Aster Analytics. This data can be passed on to Spark for analysis using deep learning techniques. Data on home sensors and thermostats can be combined with other information such as geo-location, resident demographics, and weather conditions to determine usage patterns, to predict instrument viability, and to activate household appliances in response to changing environmental conditions.

Chakravarthi said there are also a range of use cases in the retail sector and financial services.

The Teradata Aster Connector for Spark will be generally available in the fourth quarter of 2016.

This announcement is being made at the Spark Summit 2016, where Teradata is a Silver Sponsor and offering demonstrations in Booth C2.


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