Teradata has integrated Teradata VantageCloud, an cloud analytics and data platform, with Microsoft Azure Machine Learning (Azure ML).
VantageCloud’s scalability, openness and analytics – ClearScape Analytics – combined with Azure ML’s ability to simplify and accelerate the ML lifecycle could help customers unlock the full value of their data, even in the most complex and demanding environments.
Despite continued investment by organisations in AI/ML, many AI/ML initiatives struggle to get off the ground.
Teradata VantageCloud is said to deliver the enterprise-scale performance that ensures customers can execute complex analytics and AI/ML on massive datasets with the ability to incorporate the favourite data science tools of their choice, including Azure ML. This unparalleled performance, when combined with the platform’s ability to integrate preferred tools and languages, gives customers the freedom to unleash the full potential of their AI/ML investments by building, deploying and managing more high-quality models in production, faster and with confidence.
Hillary Ashton, chief product officer at Teradata, said: “As AI/ML rapidly expands in use, more organisations across industries – from healthcare to financial services to retail – are ramping up investment in AI/ML at scale to harness to the full power of their data.
“But with only half of AI/ML projects making into production, it’s become clear that organizations are not able to fully scale their advanced analytics initiatives and maximize their investments. To address this challenge, Teradata is combining Vantage Cloud’s scalability, openness and unparalleled in-database analytics with Azure ML’s acceleration and management of the day-to-day workflows of the ML project lifecycle. This gives ML professionals, data scientists, and engineers the ability to quickly and nimbly train and deploy models, and manage MLOps, leveraging the massive amount of data that Vantage ingests.”
Teradata VantageCloud and Azure Machine Learning work seamlessly, giving customers using VantageCloud on Azure the ability to tap into the power of their data. With this integration, joint customers across industries can realize the benefits from the following use cases, and much more:
- Retail – Streamline supply chains by integrating data from myriad sources to better forecast demand, improve visibility, increase real-time flexibility, and drive automation.
- Fin Serv – Enhance risk management by fully automating decisioning and integrating risk data into balance sheet optimisation.
- Healthcare – Improve patient care by using machine learning to proactively predict when medical devices may need maintenance.
Tony Surma, CTO, US global partner solutions at Microsoft, said: “Microsoft Azure Machine Learning empowers data scientists and developers to build, deploy, and manage high-quality models and accelerates time to value with support for the entire ML lifecycle. The platform is trusted by users and designed for responsible AI applications in machine learning – with built-in fairness and responsible usage for compliance.
“This reliability and trust, coupled with Teradata’s reputation for performance and stability, give our customers the confidence and support to ramp up their AI/ML initiatives to drive measurable business impact.”
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Tags: analytics, azure, machine learning, microsoft, Teradata