Data engineering often presents challenges with data quality or complex data analytics processing that requires custom logic. This is where Fabric User data functions can be used to implement custom logic into your data processes or pipelines. Here are the most common cases where Fabric User Data Functions
Microsoft Fabric is changing how we handle data engineering and data science. To make things easier, Microsoft added some cool extensions for Visual Studio Code (VS Code) that help you manage Fabric artifacts and build analytical applications. By adding these Microsoft Fabric extensions to VS Code, developers can quickly create Fabric solutions and manage their … Continue reading “Boost your development with Microsoft Fabric extensions for Visual Studio Code”
We are excited to announce the latest update to our permission model for OneLake events in the Fabric Real-Time Hub. Previously, users with the ReadAll permission, such as workspace admins, members, and contributors, could subscribe to OneLake events for items like lakehouses, warehouses, SQL databases, mirrored databases, and KQL databases. To provide more granular control, we … Continue reading “Announcing permission model changes for OneLake events in Fabric Real-Time Hub”
For nearly three years, Microsoft’s internal Azure Data team has been developing data engineering solutions using Microsoft Fabric. Throughout this journey, we’ve refined our Continuous Integration and Continuous Deployment (CI/CD) approach by experimenting with various branching models, workspace structures, and parameterization techniques. This article walks you through why we chose our strategy and how to implement it in … Continue reading “Optimizing for CI/CD in Microsoft Fabric”
Imagine a retail company that wants to gain insights into customer sentiment for each of its products. They also want to find their top-selling and least-selling products. Using Microsoft Fabric, they can build a powerful analytical application to transform their raw data into actionable insights. The process starts with ingesting raw data, such as customer reviews and sales figures, and ends with providing refined data through an API for internal use. This helps the company efficiently process customer feedback and make informed decisions to improve their products. In this blog post, we’ll dive into the architecture of an analytical application powered by Microsoft Fabric, as shown in the image, and provide a step-by-step guide on how to build it.
