Building Streaming Data Pipelines on Cloud Platform

Data is moving faster than ever, and modern systems rely on real-time insights to make critical decisions. Processing data as it arrives is essential for everything from financial fraud detection to live system monitoring. This course teaches you how to design, process, and manage continuous data streams effectively. You will explore practical techniques for handling real-time information, transitioning from traditional batch processing concepts to modern, scalable streaming architectures. What you'll learn: - Understand the fundamental concepts of streaming analytics and continuous data processing. - Build scalable data pipelines using Cloud Platform services like Pub/Sub and Dataflow. - Process continuous data streams using modern windowing, watermarks, and late-data handling techniques. - Apply modern observability patterns to monitor pipeline health, latency, and performance. - Design serverless architectures to manage real-time data ingestion without manual infrastructure provisioning. The curriculum begins with essential data engineering terminology and core streaming concepts before guiding you through practical, written exercises. You will progressively learn how to architect and deploy functional real-time pipelines by reading through step-by-step architectural breakdowns and code snippets. This course is designed for absolute beginners to streaming analytics—no prior data engineering or cloud infrastructure experience is required. Start reading today to unlock the power of real-time data processing.