“We are excited to be working with Microsoft as they continue to up the game in modern databases with the richest feature set we have seen to date. With the launch of Aginity support for Microsoft Azure SQL Data Warehouse, our customer base of 3,000 enterprises as well as that of Microsoft’s will now be able to marry the data management benefits of Microsoft’s platforms with the analytics management capabilities offered via the personal and team ‘analytic catalogs’ built in Aginity’s products,” said Paul Schaut, CEO of Aginity. “With Aginity Pro, Team and Enterprise first-ever support for a Microsoft data warehouse, a whole new class of users can now tap into the benefits of Aginity’s trusted analytics management foundation to standardize and operationalize governed analytics.”
Aginity products make every line of code searchable, reusable and easy to understand for individuals, teams and enterprises. Users dramatically accelerate the production and operationalization of analytics by reusing them rather than re-coding them, allowing them to work more efficiently and provide consistent actionable results for business growth.
Azure SQL Data Warehouse is a fully managed cloud data warehouse for enterprises of any size that combines query performance with data security. Integrated seamlessly with Aginity’s suite of products and other Azure solutions, enterprises can leverage a single holistic modern data warehouse to meet all their analytic workload demands.
“We’re pleased to be collaborating with Aginity because we share a common view of the need to bridge cloud systems with on-premises systems,” said John “JG” Chirapurath, General Manager, Azure Data and Artificial Intelligence. “Aginity’s products, combined with Microsoft, gives customers another option to discover and operationalize analytics across Microsoft’s data management, machine learning and advanced analytics services.”
Aginity empowers organizations to realize the full potential of enterprise analytics by offering the only active analytics catalog for data analysts, data engineers, data scientists, and business users. Organizations better capitalize on business opportunities, reduce business continuity risks, and dramatically accelerate deployment of analytics by reusing analytics rather than recoding.