Teradata Aster Analytics speeds time to value to benefit users of big data on Hadoop and AWS

Nik Rouda, senior analyst, ESG Global

Analytics solutions company, Teradata Corp., has announced new deployment options for Teradata Aster Analytics: Teradata Aster Analytics on Hadoop and Teradata Aster Analytics on Amazon Web Services (AWS).

Although previous versions of Aster Analytics required dedicated systems, now companies have the flexibility to accelerate valuable analytic insight from their data wherever it resides, building on their existing investments in Hadoop.

This flexibility supports Teradata’s strategy for a Hybrid Cloud architecture, the next generation of agility, flexibility, and integration between systems – and a more open approach to advanced analytics. Massive volumes of data from the Internet of Things (IoT), including sensors and digital mobile devices, have resulted in custom-tailored architecture that includes Hadoop and cloud. Teradata now provides significant options for a hybrid approach.

“Many businesses are looking for a way to integrate advanced analytics into their existing infrastructure in an orchestrated, multi-tenant environment. Teradata has just made this possible with Aster Analytics on Hadoop and Aster Analytics on AWS,” said Nik Rouda, senior analyst, ESG Global, who covers big data analytics.

“These new options allow users to provision an analytic environment and start analysing data they already have in a data lake or in the cloud. With the AWS option, they can forego large CapEx investments and pay as they go while they experiment with advanced analytic technology. In either case, these choices allow businesses to accelerate time to value and meet the analytic demands of their respective user communities – with significant economic advantages.”

In general, open source advanced analytics packages are not designed with business analysts in mind; they require specialised skills to use, deploy and maintain. And while such tools have been adapted to work with Hadoop, they are not specifically designed to run on Hadoop and, as a result, they typically require data to be extracted into a dedicated platform. These solutions are insufficiently scalable in terms of users, data and use cases.

Chris Twogood, vice president, Product and Services Marketing, Teradata
Chris Twogood, vice president, Product and Services Marketing, Teradata

“A core strength of Apache Hadoop is its extensibility and ability to embrace alternative analytic and processing engines. The addition of Teradata Aster Analytics to the industry’s offerings is a genuine advancement and gives customers a powerful new choice for demanding analytic applications,” said Mike Olson, chief strategy officer and co-founder of Cloudera, Inc.

Teradata Aster Analytics provides text, path, pattern, graph, machine learning and statistics–all within the same interface and syntax. The new options bring flexibility with clear benefits:

Teradata Aster Analytics on Hadoop

  • Broadens the use and value of the Hadoop data lake – Aster Analytics makes Hadoop accessible to general business analysts with SQL and R skills. Aster supports more users across the analytic community.
  • Runs natively in Hadoop – Rather than move data out of Hadoop into an analytic server, users can eliminate costs, delays and security risks associated with data movement and accelerate the process.
  • Quickly operationalises analytics in Hadoop – Users can instantiate development sandboxes and production environments on the same Hadoop cluster against the same data. In addition, Aster provides AppCentre to help analysts build web-based interfaces for business users.

Teradata Aster Analytics on AWS

  • Speeds time to value – Businesses can quickly provision an analytic sandbox on the cloud and leverage Aster’s prebuilt SQL-based analytics to accelerate development. If the model demonstrates value, users can move the same analytics into “production” on the cloud.
  • Boosts analytic agility – Provides the analyst with a powerful set of multi-genre analytics at scale to experiment and iterate on massive volumes of data for as long as they have the need.
  • Provides financial incentives – Allows businesses to experiment with prebuilt advanced analytics functions and their data assets without the costs of new hardware, setup or implementation.

“The ability to run Aster Analytics natively on Hadoop is a major industry breakthrough and can dramatically accelerate the return on any company’s Hadoop investment,” said Chris Twogood, vice president, Product and Services Marketing, Teradata. “Aster has always been about connecting analysts with big data at scale. But now for the first time, advanced analytics on Hadoop is fully democratised, so that business analysts as well as data scientists can access the data and analyse it with path, machine learning and graph algorithms. Our new Hadoop and AWS deployment options put business-ready, agile analytics into the hands of more users, at a faster pace, with minimal cost and risk,”

Teradata Aster Analytics on Amazon Web Services will be available in mid-September, 2016. Teradata Aster Analytics on Hadoop 7.0 will be generally available in October 2016.

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