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

Introduction of Teradata Vantage with Amazon SageMaker gives organizations ubiquitous use of advanced analytics to unlock the full power of their data

Teradata 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.

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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.

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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.

“Our enterprise customers are investing in the possibility of AI/ML to prevent fraud, reduce churn, optimize supply chains, and prevent catastrophic infrastructure failures,” said Hillary Ashton, Chief Product Officer at Teradata. “Many technology providers claim to offer AI/ML solutions to meet these critical needs – but they cannot implement them at scale. Teradata is, and always has been, an innovator in enterprise analytics and data warehousing, solving the toughest data challenges in the most complex and demanding environments. Now we are combining Vantage’s flexibility, scalability, and deep advanced analytics capabilities with Amazon SageMaker’s versatility in creating ML models to give enterprises the speed, simplicity, and scale they need to derive genuine business value from their AI investments.”

“Amazon SageMaker is one of the fastest growing services in AWS history and we are continuing to invest in expanding the service capabilities as customers further scale their machine learning models for training and inference on Amazon SageMaker,” said Omer Zaki, General Manager, SageMaker Foundations, AI Platforms at AWS.

“Being a data-driven organization allows us to make informed decisions to create a better guest and team member experience,” said Pankaj Patra, Senior Vice President and Chief Information Officer at Brinker International. “As we looked for more flexible and cost-effective ways to manage and access our data, we evaluated quite a few cloud-native providers. After careful consideration, we decided the best course of action would be to migrate to Teradata Vantage on AWS and take advantage of its offerings to support our advanced analytic goals.”

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