May 14, 2024 by Arun Ulagaratchagan 22,217 Views
Earlier this year, we hosted our first-ever Microsoft Fabric Community Conference in Las Vegas, and the response blew us away! Read about the event here. Over 4,200 attendees engaged with experts from engineering, our customers and our community to learn, engage and get hands-on experience with Fabric. We presented, demoed and discussed data warehousing, data movement, …
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In the ever-evolving landscape of data management and collaboration, the demand for seamless and secure data sharing solutions has never been greater. There are many traditional ways to share data, such as through file shares, FTP, e-mail, and APIs but most of these methods require both parties to build and maintain a data pipeline that …
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Introduction: The Fabric Readiness repository is a treasure trove of resources for anyone interested in exploring the exciting world of Microsoft Fabric. As its name suggests, this repository is designed to help communities learn about and discuss topics related to Fabric, making it an invaluable resource for user groups, online presentations, in-person conferences, and customer …
Are you interested in learning more about Data Factory, the cloud-based data integration service that allows you to create data-driven workflows in Microsoft Fabric? If so, you are invited to join our webinars, where we will show you how to use Data Factory to transform and orchestrate your data in various scenarios. Each webinar will …
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Welcome to the August 2023 update. We have lots of features this month including the new layout switcher for Power BI, SSD caching in Synapse Data Warehouse, in-line Python support for KQL in Synapse Real-time Analytics, lookup activity for Data Factory Dataflows, and much more. Continue reading for more details on our new features! Contents …
Metadata-driven pipelines in Azure Data Factory and Synapse Pipelines, and now, Microsoft Fabric, give you the capability to ingest and transform data with less code, reduced maintenance and greater scalability than writing code or pipelines for every data source that needs to be ingested and transformed. The key lies in identifying the data loading and …
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