Real-Time Data Streaming with Microsoft Fabric Eventstreams
Batch processing introduces latency between data generation and insight availability. For fraud detection, operational monitoring, and customer engagement…
12 articles
Batch processing introduces latency between data generation and insight availability. For fraud detection, operational monitoring, and customer engagement…
Enrich streaming data with reference data lookups for context-aware processing and alerting in real-time scenarios.
Eventhouse is the storage layer optimized for time-series and streaming data. It automatically indexes data for lightning-fast queries.
Eventstreams support multiple source types including Azure Event Hubs, Azure IoT Hub, and custom applications. The visual designer makes it easy to…
Eventhouses are the foundation of Real-Time Intelligence in Fabric. Today I'm exploring their architecture and capabilities in depth.
The KQL habits that keep queries over streaming telemetry fast in Fabric KQL databases and Azure Data Explorer, and the shortcuts that quietly slow them down.
How Eventstream, KQL databases, Power BI and the Data Activator preview fit together in Fabric as of January 2024, and when to choose something else.
Tomorrow we'll explore Fabric Data Science capabilities. Real Time Dashboard Documentation KQL Visualizations Dashboard Best Practices
'{ "SoftDeletePeriod": "90.00:00:00", "Recoverability": "Enabled" }' '{ "DataHotSpan": "7.00:00:00", "IndexHotSpan": "14.00:00:00" }'
'{' ' "SoftDeletePeriod": "30.00:00:00",' ' "Recoverability": "Enabled"' '}'
Real-Time Analytics in Fabric provides powerful streaming capabilities for time-sensitive workloads. Tomorrow, I will cover Power BI integration in Fabric.
The appeal of Spark Structured Streaming is that you write it almost identically to a batch Spark job. Same DataFrame API, same transformations, same Spark…