Teradata launches new analytics platform

The new solution combines both integrate Teradata and Aster technology

Tags: Data analyticsTeradata (www.teradata.com)United Kingdom
  • E-Mail
Teradata launches new analytics platform Oliver Ratzesberger, executive vice president and chief product officer at Teradata.
By  Alexander Sophoclis Pieri Published  October 24, 2017

Teradata, a global data and analytics company, recently unveiled its new offering, the Teradata Analytics Platform.

Combining the latest practices, tools and techniques, the new platform integrates not only Teradata's previous offerings into one solution, but also includes Aster technology.

Oliver Ratzesberger, executive vice president and chief product officer at Teradata, said: "In today's environment many different users have many different analytic needs ... This dynamic causes a proliferation of tools and approaches that are both costly and siloed.

"We solve this dilemma with the unmatched versatility of the Teradata Analytics Platform, where we are incorporating a choice of analytic functions and engines, as well as an individual's preferred tools and languages across data types. Combined with the industry's best scalability, elasticity and performance, the Teradata Analytics Platform drives superior business insight for our customers," he added.

The team at Teradata have also revealed that the platform will soon be able to support different engines, such as Spark, TensorFlow, Gluon and Theano. This will allow the platform to deliver scalable analytic functions, which includes path analytics, time series, as well as machine learning algorithms.

Dan Vesset, Group Vice President of IDC's Analytics and Information Management market research and advisory practice, said: "With this announcement, Teradata, one of the largest big data and analytics technology providers, will address several interrelated challenges we see facing today's digital enterprises."

"Companies are dealing with a proliferation of departmentalized analytics that are often deficient in provisioning all the relevant data at the right time. This results in sub-optimal insights and significant administrative overhead."

Add a Comment

Your display name This field is mandatory

Your e-mail address This field is mandatory (Your e-mail address won't be published)

Security code