Serverless Data Processing with Dataflow is a comprehensive 3-course series offered by Google Cloud, focusing on leveraging Google Cloud Dataflow to simplify data processing and meet the demands of a data-driven business. This specialization is designed for customers and partners seeking to advance their understanding of Dataflow.
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The course series consists of three modules: Foundations, Develop Pipelines, and Operations. These modules cover essential aspects of Serverless Data Processing with Dataflow, including Apache Beam, pipeline development, and operational best practices.
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. It provides a refresher on Apache Beam and its relationship with Dataflow, introduces the Beam Portability framework, and explores the separation of compute and storage in Dataflow. Additionally, it covers identity, access, and management tools for Dataflow pipelines, along with implementing the appropriate security model for different use cases.
In this second installment of the Dataflow course series, learners delve deeper into developing pipelines using the Beam SDK. The module covers processing streaming data, sources and sinks in pipelines, schemas for structured data, stateful transformations, pipeline performance best practices, and the use of SQL and Dataframes in Beam for business logic representation and iterative pipeline development.
The final module focuses on monitoring, troubleshooting, testing, and CI/CD for Dataflow pipelines. Learners also gain insights into deploying Dataflow pipelines with reliability in mind to maximize stability for their data processing platform.
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