by Angela Guess
According to a new article out of the company, “Teradata, the big data analytics and marketing applications company, today introduced the Teradata Aster Connector for Spark, an industry-first 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 to form a truly multi-genre advanced analytics environment. The result is that virtually anyone who can use Aster Analytics can also run advanced analytics on Spark without the need to learn or know Scala. The Teradata Aster Connector for Spark democratizes big data through self-service, business- focused, analytic solutions. By enabling ease-of-use for many business users, companies can more quickly identify revenue-driving insights and accelerate business performance. ”
The article continues, “Specifically, the Teradata Aster Connector for Spark gives users many choices and benefits: (1) Customers can now use techniques from both Aster Analytics and Spark (example, Teradata Aster nPath, used for pattern matching, and deep learning neural network analysis with Spark), and can choose the technique for implementation that generates the best insights upon evaluation. (2) Customers can pipeline various functions together in one workflow that can be executed in Aster Analytics. For example, a text parser function from Aster Analytics can be invoked, followed by a Spark machine learning algorithm, to support the development of an illuminating data model. This sequence can be replicated for other function types. (3) Customers can run a clustering algorithm in Aster Analytics, and a similar one in Spark, and compare results to see which approach is preferred.”
Photo credit: Teradata