Welcome to the September 2023 update. We have lots of features this month including updates to the monitoring hub, Fabric Metrics app, VS code integration for Data Engineering, Real-time data sharing and many more. Continue reading for more details on our new features! Contents Core Monitoring hub – column options OneLake OneLake file explorer (v.1.0.10) … Continue reading “Microsoft Fabric September 2023 Update”
Introduction This quick start is based on the official Azure Event Hubs for Kafka example, adapted to work with Microsoft Fabric. In this blog we will show you how to send data from Kafka to Synapse Real-time Analytics in Fabric. Get the sample source code from GitHub fabric-kafka-sample You will use a Fabric Eventstream to … Continue reading “Sending data to Synapse Real-Time Analytics in Fabric from Apache Kafka Ecosystems using Java”
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 … Continue reading “Real-Time Data Sharing in Microsoft Fabric “
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 … Continue reading “Microsoft Fabric August 2023 update”
AUTHOR: Guy Reginiano, Program Manager In today’s data-driven landscape, the ability to capture, analyze, and visualize vast amounts of real-time data from diverse sources is crucial for making informed decisions and gaining a competitive edge. Synapse Real-Time Analytics in Microsoft Fabric offers a comprehensive solution to this challenge. Its seamless integration with Data factory in … Continue reading “Using Data pipelines for copying data to/from KQL Databases and crafting workflows with the Lookup activity”
