September 25, 2024 by Jason Himmelstein 244,071 Views
Welcome to the September 2024 Update!
Announcements
We have a lot of exciting announcements to share with you for FabCon Europe! We’ve brought Copilot to Dataflows Gen2 and a richer Copilot experience when building and consuming Power BI Reports. With Real-Time Intelligence we have redesigned and enhanced user experience in the Real-Time hub.
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 …
Continue reading “Microsoft Fabric Data Factory Webinar Series – September 2023”
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 …
Continue reading “Create Metadata Driven Data Pipelines in Microsoft Fabric”
We are excited to announce a new high concurrency mode in Fabric for Data Engineering and Data Science. This allows users to share Spark compute across multiple notebooks within a workspace which means that you can run multiple Spark notebooks simultaneously on the same Spark session without compromising performance or security when paying for a …
