AI updates
2024-12-22 20:07:12 Pacfic

Microsoft Fabric's AI-Powered Data Analytics Enhancements - 22d
Read more: www.cio.com

Microsoft significantly enhanced its Fabric data analytics platform at its Ignite 2024 conference, unveiling key integrations and AI-powered features. A major announcement was the integration of Azure SQL, Microsoft's flagship transactional database, into Fabric. This integration allows businesses to combine real-time data with historical data within a single, AI-ready data lake called OneLake, effectively breaking down data silos that previously hindered AI applications and real-time decision-making. Further advancements include the general availability of Fabric API for GraphQL, offering support for both Azure SQL and Fabric SQL databases, improved authentication, enhanced monitoring, and CI/CD workflow integration.

The Fabric API for GraphQL update also marks a significant step forward in data accessibility and management. The general availability of this update introduces several enhancements, including support for Azure SQL and Fabric SQL databases, enabling more efficient data retrieval and analysis. Additionally, the inclusion of saved credential authentication streamlines the login process for developers, while detailed monitoring tools and CI/CD workflow integration improve the overall development and deployment experience. These features collectively contribute to a more streamlined and efficient data analytics workflow.

Further bolstering Fabric's AI capabilities, Microsoft announced the public preview of Teradata AI Unlimited through the Microsoft Fabric Workload Hub. This serverless compute engine, designed to accelerate AI innovation, provides users with access to Teradata's powerful analytics functionality, ClearScape Analytics, within the Fabric environment. This allows for flexible and cost-effective AI experimentation and model development, with the ability to easily transition successful workloads into production. The integration aims to simplify AI development and deployment by eliminating infrastructure complexities associated with traditional AI workflows.