In this session, we’ll explore how Real-Time Intelligence works, focusing on its ability to process and analyze data as it arrives for immediate insights. We’ll discuss why and when to use Real-Time Intelligence, highlighting scenarios where timely data analysis is crucial, such as fraud detection in finance by analyzing transaction patterns in real-time. Unlike batch processing, which delays insights, streaming allows for real-time ingestion, processing, and analysis of data, enabling swift business reactions.

We’ll also delve into the Real-Time Hub within Microsoft Fabric, which simplifies real-time data processing with no-code connectors, real-time dashboards, geospatial analysis, and automated trigger-based reactions. Built on OneLake, it centralizes data storage, supporting both streaming and batch data for comprehensive insights. Through demos, we’ll illustrate these concepts in action, showing how real-time data processing can enhance decision-making and operational efficiency, and how AI and machine learning advancements in Microsoft Fabric enable users to create sophisticated dashboards and analytics without needing deep technical expertise in KQL or SQL.