Microsoft

Snowflake on Microsoft Azure can power all your workloads—from data warehousing to AI, machine learning, applications, and everything in between—simplifying data proliferation and collaboration across your most critical use cases.

With a multitude of integrations to Microsoft’s industry-leading Cloud products like Azure OpenAI, Azure ML, Power BI, Power Apps and more, Snowflake’s Data Cloud is easy to use, fast and frictionless to deploy, and feature-rich to empower your data-driven organization.

The Snowflake and Microsoft Partnership

Listen in on this one-on-one conversation between the top two executives of Snowflake and Microsoft as they discuss the expanded partnership between their companies.

Snowflake's CEO Frank Slootman and Microsoft's CEO Satya Nadella discuss how Snowflake’s expanded partnership with Microsoft will combine Snowflake’s Data Cloud expertise with Microsoft’s cloud technologies and AI capabilities to help customers build intelligent solutions, especially as we enter the next wave of generative AI.

SNOWFLAKE AND MICROSOFTLEARNING HUB

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Did you know that you can implement Generative AI in Snowflake with Azure OpenAI? This blog covers how Azure OpenAI provides a new way to interact with the data in Snowflake.

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Join this virtual hands on lab where partner engineers from Microsoft and Snowflake will introduce the common business cases for using Generative AI and discuss the common patterns for using Snowflake with Azure Open AI to generate insights from your data in Snowflake.

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In this quickstart you will learn how to build an architecture that demonstrates how to use Azure OpenAI with an AzureML Prompt Flow, AzureML Notebooks, Snowflake and the Snowflake + AzureML Connector to quickly generate results.

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Snowpark and AzureML can efficiently be used to prepare data, train models and deploy a model for inference all while leveraging the rich features of both platforms. This blog explores how to work with Snowpark in conjunction with AzureML.

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Join ML experts from Snowflake and Microsoft to:

Break down Snowflake platform components, including Snowpark, to help you think about your data and feature pipeline architecture
Get deep insight into updates on integrations that streamline how you bring features into your models using Azure Machine Learning
Learn how to use the joint solution through a walk through demo

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This quickstart is designed to serve as an introduction to using AzureML with Snowpark for model development and deployment to Snowflake. The idea is that users can build off this quickstart or integrate components into their existing AzureML workloads.

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Back in March, Power BI unveiled a public preview of query parallelization improvements for DirectQuery mode that significantly boost performance in certain scenarios.

This blog post evaluates one such scenario, using time intelligence measures, and how it benefits from this enhancement. Spoiler: we saw just shy of a 5x performance gain while putting query parallelization to the test against Snowflake.

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Join this instructor-led hands-on lab with Microsoft and Snowflake to learn how to access all relevant data from a single source and turn data into insights through the Power BI integration.

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In this lab, you'll learn how to access all relevant data from a single source and turn data into insights through the Microsoft PowerBI integration.

Access first party data seamlessly in Snowflake Leverage the Data Marketplace to query live POS data from 3rd party providers Set up self-serve analytics via Power BI.

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The Snowflake Connector for Microsoft Power Platform provides instant access to up-to-date data within your Snowflake instance without manually integrating against API endpoints. Now anyone can easily build low-code applications or workflows on Power Platform that leverage Snowflake data without any previous technical or app development experience.

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This quickstart will teach you how to configure a connection between Power Automate and Snowflake and run a simple query from Power Automate to query Snowflake data.

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