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The rebranding of Teradata's core product as the Teradata Analytics Platform is meant to reposition it from being an enterprise data warehouse. Announced in October 2017, the move represents the next modernizing step for an established company.


  • The Teradata Analytics Platform is the continuation of a broader shift in the business, as the the last year and a half has seen a radical restructuring of licensing and deployment options.
  • The "new" Teradata is focused on solving the analytics challenges for the largest, most demanding enterprise use cases. The Teradata Analytics Platform aims to serve the full enterprise from self-service users to traditional BI and advanced analytics users.
  • The more Teradata can expand the platform’s tool bench, the more data science users will be compelled to stay in the environment – a key objective if IT and data scientists are to align objectives and cooperate in achieving data governance goals.

Features and Benefits

  • Evaluates the Teradata Analytics Platform's role in Teradata's current business strategy and pricing structure.
  • Identifies key components of the Teradata Analytics Platform architecture, and describes how the former Aster offering fits into this structure.
  • Evaluates the similarities between the Teradata Analytics Platform and an enterprise data lake.
  • Identifies the ideological and practical differences between the needs of data scientists and the IT function of the enterprise, and describes how a single analytics platform helps meet the needs of both.
  • Assesses the features and functionality that will be necessary for Teradata to add to its platform in order to meet the needs of the market.

Key questions answered

  • How does the Teradata Analytics Platform offering fit into Teradata's modern, evolving business strategy?
  • What is the target market for the Teradata Analytics Platform, and how is Teradata catering to this audience?
  • What are the core components, engines, and functionality that comprise the Teradata Analytics Platform?
  • How is the Teradata Analytics Platform similar to – or different from – an enterprise data lake composed of Hadoop or cloud storage?
  • How will the Teradata Analytics Platform help bridge the requirements of IT and data scientists, helping the enterprise operationalize the data science process?

Table of contents

Ovum view

  • Summary
  • Part of the onward drive to modernize the company
  • The Teradata Analytics Platform: another data lake?
  • Bridging the divide between IT and data scientists


  • Further reading
  • Author

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