Introduction to Real-Time Dashboards | Microsoft Fabric Tutorial

In this tutorial, Manuel Quintana of Pragmatic Works provides a step-by-step guide on how to create real-time dashboards in Microsoft Fabric. This tutorial is part of a series that explores real-time intelligence (RTI), which includes understanding streaming data and working with KQL (Kusto Query Language) to create interactive dashboards. If you haven't watched the previous tutorials in the series, it’s recommended to check them out to get familiar with the foundational concepts of RTI.

What Are Real-Time Dashboards?

A real-time dashboard is a powerful tool used to visualize live data and display insights in a way that's easy to understand. Similar to dashboards in PowerBI, real-time dashboards in Microsoft Fabric allow organizations to present their data dynamically, with tiles that can be customized to display specific insights. However, instead of working with static data, real-time dashboards work with streaming data, or data that's continuously updated in real time.

Creating a Real-Time Dashboard

To create a real-time dashboard in Microsoft Fabric, follow these general steps:

• Set up the environment: First, ensure that you are working with the right dataset. In this tutorial, Quintana uses weather data, accessed through Microsoft Fabric’s event house KQL database.
• Create a new dashboard: Once you’ve connected to your data source, click on "new item" and search for the dashboard option. After creating a blank dashboard, you’ll enter the edit mode where you can begin adding tiles.
• Connecting to a Data Source: You can either connect to an external KQL database, such as Azure Data Explorer, or use an internal source like the event house database. In this example, Quintana connects to the event house KQL data source, ensuring it matches the workspace being used for the tutorial.

Adding Tiles to the Dashboard

In real-time dashboards, tiles are used to display different types of data insights. Each tile can be configured with a KQL query that pulls data from a specified source and presents it visually. Quintana demonstrates how to create a tile using a KQL query to retrieve the number of weather events. The process involves:

• Writing a KQL statement that queries the data.
• Choosing a visualization type for the tile, such as a stat card, column chart, or pie chart.
• Configuring the tile’s appearance and layout to ensure the data is presented clearly and meaningfully.

In this example, the first tile created shows the count of weather events. Quintana opts to display it as a stat card for easy viewing of a single value. This visual element helps monitor real-time data, and in a live scenario, it would automatically refresh to reflect any new incoming data.

Working with Multiple Tiles

Real-time dashboards often consist of multiple tiles, each displaying different aspects of the data. Quintana goes on to add more tiles that break down the weather events by type and region, allowing viewers to see patterns such as the number of storms in different states. Different visualizations such as column charts and tables can be applied to help present this data effectively.

Additional Customization and Settings

One of the key features of real-time dashboards is the ability to customize how data is displayed. Quintana explains how to:

• Configure auto-refresh settings for each tile, allowing the dashboard to continuously update with the latest data.
• Use different visualizations depending on the type of data being displayed (e.g., a pie chart for categorical data, or a bar chart for comparisons).
• Manage multiple data sources if needed, creating a multi-source dashboard that pulls data from various databases.

Additionally, Quintana demonstrates how to manage access to the dashboard by sharing it with other users. This enables teams to collaborate on data insights and make decisions based on real-time information.

Conclusion

The real-time dashboard is an essential tool for organizations that need to visualize data in motion. By leveraging Microsoft Fabric's event house KQL database, you can create dashboards that update automatically, offering valuable insights at a glance. Whether you're tracking weather events or any other type of streaming data, this tutorial equips you with the knowledge to build an effective real-time dashboard. As Quintana highlights, understanding KQL and the power of real-time intelligence will help you present data more effectively and make data-driven decisions faster.

Don't forget to check out the Pragmatic Works' on-demand learning platform for more insightful content and training sessions on Fabric and other Microsoft applications. Be sure to subscribe to the Pragmatic Works YouTube channel to stay up-to-date on the latest tips and tricks.