Enroll Course: https://www.coursera.org/learn/developing-pipelines-on-dataflow
The ‘Serverless Data Processing with Dataflow: Develop Pipelines’ course on Coursera is a comprehensive deep dive into building efficient data pipelines using Apache Beam and Google Cloud Dataflow. As the second installment in the Dataflow series, this course is ideal for data engineers, developers, and cloud practitioners looking to enhance their skills in stream and batch data processing.
The course begins with a robust review of Apache Beam concepts, ensuring learners have a solid foundation to build upon. It then explores advanced topics such as processing streaming data using windows, watermarks, and triggers—crucial techniques for managing real-time data streams effectively.
One of the highlights of this course is its in-depth coverage of sources and sinks, including practical examples with Text IO, FileIO, BigQuery, Pub/Sub, Kafka, and more. Learners will also understand how to express structured data using schemas and implement stateful transformations with State and Timer APIs.
Additionally, the course offers best practices to optimize pipeline performance, introduces new APIs like Dataflow SQL and Dataframes for business logic representation, and demonstrates how to leverage Beam notebooks for interactive development.
Overall, this course is a valuable resource for mastering serverless data processing. I highly recommend it to anyone looking to elevate their data pipeline skills and harness the power of Google Cloud Dataflow for scalable, efficient data processing.
Enroll Course: https://www.coursera.org/learn/developing-pipelines-on-dataflow