Teradata Accelerates Enterprise Scalability of Artificial Intelligence and Machine Learning Projects in Teradata Vantage with Amazon SageMaker

Teradata (NYSE: TDC) today announced the integration and general availability of the Teradata Vantage multi-cloud data and analytics platform with Amazon SageMaker, the industry’s most complete end-to-end machine learning (ML) service. By uniting the scalability and openness of Vantage with the intuitive ML model capabilities of Amazon SageMaker, Teradata and Amazon Web Services (AWS) are solving the scalability dilemma for enterprises worldwide.

This move supports Teradata’s analytics framework, Analytics 123 which gives organizations that are challenged with production-level artificial intelligence (AI)/ML initiatives a step-by-step solution for deploying analytical models at scale. Together, the Analytics 123 framework and the integration of Vantage with Amazon SageMaker drive faster time-to-value and greater return on investment (ROI).

Despite massive investments in AI/ML and other advanced analytics, many organizations have yet to deploy these solutions widely and are struggling to see the true value of their promise. This is because data preparation for AI/ML is time consuming and costly, with data wrangling still accounting for up to 80% of the cost and effort of analytic projects. In the Gartner report "Top Trends in Data and Analytics for 2021" they say "Many organizations struggle to scale their AI prototypes and pilots to full production and wider usage, and often underestimate the challenge of deploying and integrating AI with other systems. According to the 2020 Gartner AI in Organizations Survey, only 53% of prototypes are eventually deployed." And certainly not at scale and across organizational silos.

Teradata Vantage delivers enterprise-scale performance to ensure that even the largest customers can execute complex analytics on massive datasets while using their favorite data science tools and languages - such as Amazon SageMaker. Amazon SageMaker enables developers to create, train, and deploy AI/ML models on the cloud, embedded systems, and edge devices. Tens of thousands of active customers use Amazon SageMaker to train models with billions of parameters to make hundreds of billions of predictions every month.

Vantage and Amazon SageMaker work seamlessly, giving customers the ability to continuously score complex ML models at scale. AI/ML projects can move into wide-scale production in weeks instead of months and organizations can score data, like customer or parts information, in minutes instead of hours and days. The result is that customers can now rapidly accelerate their AI/ML projects to deliver data-driven insights and realize real-world business outcomes.