Serverless Data Processing with Dataflow Foundations

Modern businesses generate massive amounts of data every second, but extracting value from this data requires robust, scalable pipelines that can process information without administrative overhead. This text-only course introduces you to the core principles of serverless data engineering using Dataflow, enabling you to focus on writing pipeline logic instead of managing servers. You will understand how to build efficient data pipelines that automatically scale to meet your business demands. What you will learn: Understand the foundational concepts of serverless architecture and managed data pipelines; Learn Apache Beam programming model basics to write portable data processing pipelines; Create batch pipelines to process historical data stored in cloud storage; Design streaming pipelines to handle real-time data ingestion and transformation; Practice handling late-arriving data using windowing, triggering, and accumulation concepts; Configure pipeline monitoring, logging, and performance tuning for production environments. The course begins with essential data engineering terminology and foundational concepts before guiding you through the step-by-step design of batch and streaming pipelines. This course is designed for beginner data engineers, software developers, and database administrators who want to transition to cloud-based data processing. No prior cloud data engineering experience is required, though a basic understanding of programming logic and SQL is helpful. Start building scalable, serverless data pipelines today.