Teradata Collaborates with Microsoft to Offer VantageCloud Lake on Azure, Enabling AI/ML at Scale Throughout the Enterprise

Teradata (NYSE: TDC) today announced it will offer Teradata VantageCloud Lake on Microsoft Azure, opening up new markets, new capabilities, and new use cases. This makes Teradata’s modern cloud-native architecture, and robust analytics capabilities in ClearScape Analytics, available to customers interested in using harmonized data and trusted AI to drive faster innovation.

ClearScape Analytics, the powerful, open, and connected analytics framework that is included with VantageCloud Lake on Azure, is enhanced by integration with Microsoft services such as Azure Machine Learning (ML). This means VantageCloud Lake on Azure is designed to dramatically increase the ability of mutual customers to deploy and manage AI/ML, including generative AI, within their businesses today.

The advent of generative AI has ignited a race to use the technology in organizations of all sizes. IDC recently surveyed CIOs, CDOs, and CFOs, and found that more than half expect significant pressure to use generative AI capabilities in the next six to twelve months. In fact, nearly 95% expect to feel at least some pressure to implement and/or use generative AI.*

“Generative AI and large language models (LLMs) are set to fundamentally transform every industry, dramatically amplifying what people can achieve,” said Hillary Ashton, Chief Product Officer at Teradata. “Teradata and Microsoft are among the leading companies with the expertise and innovative technology to help organizations get ahead of this opportunity and make significant improvements across business performance and customer experiences. VantageCloud Lake on Azure provides the backbone to deliver trusted AI and ML across the entire enterprise.”

VantageCloud Lake on Azure

With the availability of VantageCloud Lake on Azure, Teradata and Microsoft customers will benefit from modern cloud-native architecture, including the full separation of compute and storage, as well as independent, elastic, and multi-cluster compute – all against Azure Data Lake Storage. This cost-effective, dynamically scalable solution with self-service provisioning enables Azure customers to execute a wide array of analytic workloads (including AI/ML) at scale, with harmonized data across the enterprise.