I just stepped off the stage at SQLSaturday Atlanta and the energy around Microsoft Fabric is absolutely electric. Between the deep-dive sessions and the hallway conversations, one question kept coming up: “How do we make our data orchestration more efficient?”

In the world of Synapse and Data Factory, we’ve been conditioned to “Poll.” We set a schedule to check a table every 15 minutes, 24/7. But in a Capacity-based world like Fabric, “Polling” is essentially a tax on your resources.

Today, I’m sharing the framework I demoed in Atlanta – moving from expensive “Ghost Pipelines” to a lean, event-driven architecture that only works when there is a “doorbell” to answer.

In this blog, I’ll walk you through how to build a Real-Time Indian Railways Train Running Status Dashboard using Microsoft Fabric.

We’ll stream live railway data from a public API into Eventstream, store it in Eventhouse, transform it using KQL, and finally visualize it in a real-time dashboard.

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:  

1. You have streaming ingestion with variety of consumers for the data.
2. 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.

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.

Fabric Real-Time Intelligence isn’t just for developers. Learn how to start small, stay curious, and use resources like the Kusto Detective Challenge and Microsoft’s tutorial to build dashboards that drive action in real time.

Learn how to configure an event-driven data pipeline that automatically gets triggered when a new file lands in OneLake or Azure Blob Storage, to ingest and transform the new file.

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!

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. 

If you've ever seen a demo of Microsoft Fabric's Data Activator, it probably involved simulated data and pre-recorded spikes in dashboards. While the technology is undeniably powerful, it's often hard to connect those demos to something tangible.

In this post, I’ll walk you through how I used Data Activator, Azure Event Hub, and a Raspberry Pi connected to my electric panel to monitor the real-time energy usage of my house. This isn't just a mock-up — I can trigger real alerts by turning on real appliances in my kitchen.

Following quentincarton's deep dive into integrating ServiceNow with Microsoft Fabric Real Time Intelligence, this follow-up explores how to truly harness that data once it's flowing. From real-time dashboards and text analytics to automated alerts and Power BI reporting, discover how to turn your ServiceNow incidents into actionable insights—live, as they happen. Learn how Eventhouses and Notebooks in Fabric can help you extract key phrases, visualize trends, and even trigger downstream processes in real time.

🔍Ready to see your ticketing data in a whole new light? Dive into the possibilities!

When monitoring real-time data, you want updates as soon as new data comes in, but without unnecessary refreshes. This is where page refreshes based on change detection in Power BI become useful.

For example, if new data arrives every five minutes, refreshing a report ten times per minute is inefficient. Power BI’s change detection refresh option updates the page only when a specific field changes!

Migrating to Microsoft Fabric Real-Time Intelligence (RTI) from Azure Data Explorer (ADX) offers several benefits for organizations looking to enhance their data analytics capabilities. This article outlines how to efficiently migrate from ADX to Fabric RTI. Dive into the future of data analytics with Fabric RTI and see how it can transform your business operations.

Join a Microsoft Fabric Reddit Ask me Anything on March 5th at 10 AM PT with the Real-Time Intelligence team! 

Discover how to enhance your Azure/Fabric Data Factory pipelines with real-time telemetry using Microsoft Fabric RTI. Learn to seamlessly send diagnostic data to Eventhouses, enabling you to create dynamic dashboards and alerts for better performance monitoring and error troubleshooting. This guide walks you through setting up a flexible, schema-agnostic table and integrating it with your pipelines for instant insights. Transform your data analytics with ease and efficiency—explore the full potential of Fabric Real Time Intelligence today!

So, you’ve started exploring real-time intelligence in Fabric and maybe even followed the Microsoft tutorial to implement a real-time solution. Now, you’re looking to analyze and visualize that data, and that’s where KQL (Kusto Query Language) comes in.

When I started, I struggled a bit, so I thought it would be a good idea to provide some basic queries (and explain what they do) for people who want to get started but are unfamiliar with querying data.

Real-time dashboards are perfect for tracking what's happening and allowing users to react when action is needed.

But how can you ensure that users know when it's time to act? One approach is to send alerts, such as emails or Teams messages (using Activator). Another effective method is to highlight critical data points directly on the dashboard, and this is where conditional formatting comes into play. Conditional formatting helps emphasize the most important information, allowing users to identify and respond to key issues quickly.

Discover how to effortlessly recreate your ADX dashboards as Real-Time Dashboards in Microsoft Fabric—without moving your data. Connect directly to your ADX clusters, leverage powerful Fabric features like permissions management and real-time collaboration, and unlock new possibilities for data-driven insights.

Much of the conversation around Microsoft Fabric rightly focuses on gaining insights from our data. But what if the insights we reveal demand immediate action to mitigate a problem in real-time or, better yet, prevent a problem from occurring in the first place? Data Activator allows us to do just that within Real-Time Intelligence in Microsoft Fabric. If you're reading this and saying "what's Data Activator?", you've come to the right place.

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.

You might be familiar with setting an alert on a visual in a Power BI Dashboard, but Data Activator can provide more functionality and add value to your alerts!

The Real-Time Intelligence service in Fabric can help you deploy an Event Hub directly with a few clicks with your mouse.

The Eventstream processor is your go-to service to get this done - read this post to learn how to deploy it and how to use it.

I work with a lot of clients that are creating analytic systems. They all collect large numbers of data points and analyze them. Most do a fairly good job with it.

Bue one area that I see very few handling well, is the data that is missing, rather than just the data that is present. There's a huge difference between data that arrived, and is odd, and data that just didn't arrive at all.

One tool that's great at working with streams of data is the Real Time Intelligence workload for Microsoft Fabric. And it's also great at working with data that is missing from those streams.

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.