Handling Multiple Schemas in Eventstream for Azure Event Hub and Azure IOT Hub data sources
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!Eventhouse vs Lakehouse - When to Use Which in Microsoft Fabric?
Microsoft Fabric offers multiple storage and analytical engines. This blog helps you make the right architectural choice early on and save them massive migration efforts later. In this blog, I’ll walk you through the differences between these two powerhouses, look at real-world challenges, map out concrete scenarios, and give you a definitive comparison framework so you can choose the right tool for the job.🚦From Signals to Insights: Bengaluru Smart City Traffic Updates with Fabric Real-Time Intelligence
In this blog, we will build a Bengaluru Smart City Traffic Updates Dashboard using Microsoft Fabric Real-Time Intelligence. We'll simulate live traffic signals from major Bengaluru junctions, stream events into Fabric, store them in a KQL database, and create an interactive real-time dashboard that provides actionable traffic insights. By streaming events into Fabric and leveraging powerful analytics, you’ll see how raw signals can be transformed into actionable insights for smarter urban mobility.
Optimizing Real-Time Analytics in Microsoft Fabric RTI with Follower and Read-Optimized Databases
This article discusses about an architectural pattern to achieve better performance when trying to work with traditional relational database schema in Microsoft Fabric Real Time Intelligence (RTI). A common scenario is that you have Fabric as the enterprise data platform that ingests data from a live system running at scale. This article addresses two common requirements: You have streaming ingestion with variety of consumers for the data. You have use cases that demand fast response time even when the query is joining huge tables. The pattern discussed here uses a database shortcut in Fabric RTI, also known as a follower database, and a read-write database. With the database shortcut, each downstream system gets dedicated capacity and SLAs. With a read-write database, data can be denormalized and stored in a read-optimized format to improve real time query performance.Building a Real-Time Weather Dashboard in Microsoft Fabric: Step-by-Step Guide
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.
Eventhouse and its best practices
As data volumes grow and real‑time insights become critical, choosing the right analytics platform matters. Eventhouse simplifies large‑scale data ingestion and querying while offering smart controls for cost, performance, and reliability. In this article, we dive into how Eventhouse works and the best practices that help you get the most value from it.Comparing JSON in Eventhouse Without Defining Schema
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.Real-Time Analysis of Microsoft Form Responses with Microsoft Fabric Real-Time Intelligence
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.
