Introduction

Imagine you're a data analyst for a delivery company, responsible for monitoring package delivery performance across your network of distribution centers, delivery vehicles, and customer routes. Your operations team needs to know immediately when delivery delays occur, which routes are experiencing issues, and how customer satisfaction is trending in real time. Currently, your delivery reports are generated overnight, meaning by the time you identify a problem—such as a vehicle breakdown or weather-related delays—hundreds of packages might already be behind schedule and customers are left waiting without updates. You need continuous monitoring of delivery trucks, customer feedback systems, and warehouse scanners to track package movements and delivery performance as events happen, not hours later.

In this scenario, Real-Time Intelligence in Microsoft Fabric can be used to help you work with streaming data from GPS trackers on delivery vehicles, package scanning systems, and customer notification platforms as events occur. Unlike traditional batch processing that shows historical snapshots of delivery status, Real-Time Intelligence could help you analyze package movements and delivery performance as it happens. This approach could help you spot route delays quickly, estimate delivery windows based on current conditions, and set up automated customer notifications while creating workflows for route optimization.

By the end of this module, you'll understand how Microsoft Fabric Real-Time Intelligence components work together to create real-time analytics solutions, how to ingest, process, store and query real-time data, and how to visualize data in motion and automate responses to changing conditions.