Microsoft Fabric seamlessly integrates with generative AI to enhance data-driven decision-making across your organization. It unifies data management and analysis, allowing for real-time insights and actions.
With Real Time Intelligence, keeping grounding data for large language models (LLMs) up-to-date is simplified. This ensures that generative AI responses are based on the most current information, enhancing the relevance and accuracy of outputs. Microsoft Fabric also infuses generative AI experiences throughout its platform, with tools like Copilot in Fabric and Azure AI Studio enabling easy connection of unified data to sophisticated AI models.
Check out GenAI experiences with Microsoft Fabric.
Classify and protect schematized data with Microsoft Purview.
Connect data from OneLake to Azure AI Studio.
Watch our video here:
QUICK LINKS:
00:00 — Unify data with Microsoft Fabric
00:35 — Unified data storage & real-time analysis
01:08 — Security with Microsoft Purview
01:25 — Real-Time Intelligence
02:05 — Integration with Azure AI Studio
Link References
This is Part 3 of 3 in our series on leveraging generative AI. Watch our playlist at https://aka.ms/GenAIwithAzureDBs
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Video Transcript:
-If you want to bring custom Gen AI experiences to your app so that users can interact with them using natural language, the better the quality and recency of the data used to ground responses, the more relevant and accurate the generated outcome.
-The challenge, of course, is that your data may be sitting across multiple clouds, in your own data center and also on the edge. Here’s where the complete analytics platform Microsoft Fabric helps you to unify data wherever it lives at unlimited scale, without you having to move it.
-It incorporates a logical multi-cloud data lake, OneLake, for unified data storage and access and separately provides a real-time hub optimized for event-based streaming data, where change data capture feeds can be streamed from multiple cloud sources for analysis in real time without the need to pull your data. Then with your data unified, data professionals can work together in a collaborative workspace to ingest and transform it, analyze it, and also endorse it as they build quality data sets.
-And when, used with Microsoft Purview, this can be achieved with an additional layer of security where you can classify and protect your schematized data with protections flowing as everyone from your engineers, data analysts to your business users works with data in the Fabric workspace. Keeping grounding data for your LLMs up to date is also made easier by being able to act on it with Real Time Intelligence.
-For example, you might have a product recommendation engine on an e-commerce site and using Real Time Intelligence, you can create granular conditions to listen for changes in your data, like new stock coming in, and update data pipelines feeding the grounding data for your large language models.
-So now, whereas before the gen AI may not have had the latest inventory data available to it to ground responses, with Real Time Intelligence, generated responses can benefit from the most real-time, up-to-date information so you don’t lose out on sales. And as you work with your data, gen AI experiences are infused throughout Fabric. In fact, Copilot in Fabric experiences are available for all Microsoft Fabric workloads to assist you as you work.
-And once your data set is complete, connecting it from Microsoft Fabric to ground large language models in your gen AI apps is made easy with Azure AI Studio, where you can bring in data from OneLake seamlessly and choose from some of the most sophisticated large language models hosted in Azure to build custom AI experiences on your data, all of which is only made possible when you unify your data and act on it with Microsoft Fabric.
