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In this blog, I’ll walk you through how to build a Real-Time Weather Analytics Dashboard in Microsoft Fabric by streaming public weather feeds into Eventstream, storing them in Eventhouse, and finally visualizing them in a Real-Time Dashboard.

 

For this example, I’m using Bengaluru, India and several of its suburban locations.

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One of the challenges with streaming data is that data comes in a variety of schemas, which can be dynamic and are not always predictable. As applications and data structures change, schema values can sometimes be wildly different across devices or event inputs. Recently a customer reached out with several questions on this common problem. With the capabilities in Fabric Real Time Intelligence we can flexibly ingest this data. Enough of the background let’s get to the problem!

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When working with raw JSON data in Eventhouse, one common challenge is comparing two records to identify what changed—especially when the structure isn’t fixed. Fields may appear, disappear, or shift in type, making traditional column-based comparisons brittle or outright impossible. This post will walk you through how to compare two JSON arrays and find what changed without needing to define the schema first. 

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Real-Time Intelligence might mean different things to different people but I try to help explain what it means in the context of Microsoft Fabric.

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Collecting data using Microsoft Forms is a common practice, and analyzing the responses in real time is incredibly valuable. In the past, many users relied on the Streaming Semantic Model (Dataset) in Power BI to capture and visualize live data. However, with the recent retirement of this feature, it's time to use Microsoft Fabric Real-Time Intelligence as the new solution for live reporting.

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With the Fabric Real-Time Intelligence service we have the KQL data processing engine. This engine comes with an extensive set of security features for reading and manipulating data.

 

This blogpost gives you an overview of the different features.

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