Teradata Adds Sophisticated New Capabilities To Its Analytics

Chris Preimesberger,
teradata universe

Teradata is providing a package that solves the problem enterprises have of stitching together all the required software to manage an analytical ecosystem from multiple sources and vendors

Teradata, known widely for its data warehouses but which has been expanding its business to include data analytics software and services, introduced two new additions to its product lineup Oct. 23.

Believe it or not, Teradata—though known for its storage-based analytics products—had not had a single platform that incorporated all its key analytics tools until now.

At its partner conference in Anaheim, Calif., Teradata said that its rejiggered analytics platform is designed to enable users throughout an enterprise to deploy their preferred tools and languages, at scale, across multiple data types. Teradata Analytics Platform accomplishes this by embedding the analytics engine close to the data, which eliminated the need to move data and allows users to run their analytics against larger data sets with greater speed and frequency.

Secondly, Teradata introduced something called IntelliSphere, describing it as a “single software portfolio powering the analytical ecosystem.” In plain English, this means that Teradata finds out what the customer wants and then supplies all the software and serviced needed, whether or not it’s on the Teradata shelf. This became available on Oct. 23.

Machine learningFinds Data Wherever It Is

The Teradata Analytics Platform, which finds data wherever it is in the customer’s IT system and moves its application to those locations, will become available later this quarter on an early-access trial basis.

Teradata’s always provided analytics of various kinds for its customers. What’s different here?

“What we’re doing is raising the bar,” Imad Birouty, Director of Product Marketing, told eWEEK. “We’re taking the analytics the company has done previously and bringing advanced analytics functions into it—things like path analysis, graph analysis, sessionization, machine learning algorithms. We’re saying that these advanced functionalities are not just for the data scientist, or select few people.

“We’re bringing those into the warehouse and then extending the warehouse, so that we can create an architecture underneath where we can reach out to other analytic tools like Spark, Tensorflow, Aster or others, and make those function available to all the users in the warehouse.”

Enterprises are now attempting to stitch together all the required software to manage an analytical ecosystem from multiple sources and vendors. It can get very complicated and difficult to manage.

Analytics at Scale

IntelliSphere offers advanced analytics at scale, Teradata Executive Vice President and Chief Product Officer Oliver Ratzesberger said.

“With IntelliSphere, companies no longer need to purchase separate software applications to build and manage their ecosystem. Companies can design their environment to realize the full potential of their data and analytics, with a guarantee that future updates can be leveraged immediately without another license or subscription,” Ratzesberger said.

Because businesses are now requiring greater analytic agility, more analytics users are asking for access to a larger number of analytic tools and increased data, Ratzesberger said. Thus architectures capable of handling this demand are now a business requirement. This forces companies to deploy and manage large, multi-system analytical platforms typically comprised of a mix of IP from different solution providers and the open source community.
 
Teradata IntelliSphere is composed of ten software components, including:

As new software solutions are released in the future they will become part of the IntelliSphere bundle, so customers will get the benefit of access to new Teradata software products under their existing licensed bundle, Birouty said.

The Analytics Platform eliminates the need to store data across multiple engines, allowing analysts to iterate and refine their analysis.
 
Business analysts and data scientists use many different analytic tools and languages. These tools and languages are constantly changing and are increasingly open source. The Analytics Platform provides support for Python, R, SAS, or SQL. Analytic users can also use their favorite tools such as Jupyter, RStudio, KNIME, SAS, and Dataiku. Teradata AppCenter allows analysts to share analytic applications with peers by deploying reusable models in a web-based interface, giving self-service access to business users.

Originally published on eWeek. 

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