Data management platform SAS has chosen Microsoft as its preferred cloud provider and will integrate its analytical products into the Azure portfolio.

The two firms also plan to launch joint services for their customers. 

The partnership will enable customers to run SAS workloads in the cloud, expanding their business operations and accelerating digital transformations, according to SAS. The company’s analytical products, used in areas such as health care, financial services and other industries, will also be migrated into Azure. 

The partnership builds on previous SAS integrations across Microsoft‘s Azure, Dynamics 365, Microsoft 365 and Power Platform and supports the companies shared vision to further «democratise» AI and analytics, according to SAS.

«SAS and Microsoft have a shared vision of helping customers accelerate their digital transformation initiatives,» said Oliver Schabenberger, SAS CTO and COO. «We both understand that it is about the enrichment of data and improving lives through better decisions. 

«Partnering with Microsoft gives customers a more seamless path to the cloud that provides faster, more powerful and easier access to SAS solutions and enables trusted decisions with analytics that everyone – regardless of skill level – can understand.»

SAS is a 44-year-old company based in North Carolina that boasts a wealth of high profile clients, including the likes of Allianz, Honda, HSBC, Lufthansa and Nestlé. It provides a number of different tools and services, but mostly its focus on data management and actionable analytics.

«Through this partnership, Microsoft and SAS will help our customers accelerate growth and find new ways to drive innovation with a broad set of SAS Analytics offerings on Microsoft Azure,» said Scott Guthrie, Microsoft’s executive VP of Cloud and AI. 

«SAS, with its recognised expertise in analytics, data science and machine learning, is a strategic partner for Microsoft, and together we will help customers across dozens of industries and horizontals address their most critical and complex analytical challenges.»