Real-time Data Processing with Azure Databricks

Real-time data matters. This course will teach you how to build scalable, real-time data pipelines using Azure Event Hub and Databricks for event-driven analytics and anomaly detection

What you'll learn

Modern applications need immediate insights from data—not hours or days later. But real-time data processing in the cloud can be tricky to set up and scale efficiently. In this course, Real-time Data Processing with Azure Databricks, you’ll gain the ability to design and build scalable, real-time data pipelines using Azure-native tools.

First, you’ll explore the fundamentals of real-time streaming and how Azure Event Hub enables ingestion of high-throughput, real-time data. Next, you’ll discover how to set up Azure Databricks for real-time processing using structured streaming, how to handle schema evolution, and how to implement anomaly detection with ML models. Finally, you’ll learn how to monitor, optimize, and scale your streaming workloads using checkpointing, autoscaling, and Azure-native monitoring tools.

When you’re finished with this course, you’ll have the skills and knowledge of Azure Databricks streaming needed to build powerful, real-time data pipelines in a production-ready environment.