Apache Beam | A Hands-On course to build Big data Pipelines

Build Big data pipelines with Apache Beam in any language and run it via Spark, Flink, GCP (Google Cloud Dataflow).

Created by: J Garg - Real Time Learning
Data Engineering, Analytics and Cloud Trainer

What Will I Learn?

• Learn Apache Beam - A portable programming model whose pipelines can be deployed on Spark, Flink, GCP (Google Cloud Dataflow) etc.
• Understand the working of each and every component of Apache Beam with HANDS-ON examples.
• Learn Apache Beam fundamentals including its Architecture, Programming model, Pcollections, Pipelines etc.
• Multiple PTransforms to Read, Transform and Write the processed data.
• Advance concepts of Windowing, Triggers, Watermarks, Late elements, Type Hints and many more.
• Load data to Google BigQuery Tables from Apache Beam pipeline.
• Build Real-Time business's Big data processing pipelines using Apache Beam.
• Data-sets and Beam codes used in lectures are available in resources tab.

Requirements

• Basic knowledge of Distributed data processing architecture.
• Basic knowledge of Python.

Target audience

• Students who want to learn Apache Beam from scratch to its Live Project Implementation.
• Data engineers who want to build Unified & Portable Big data processing pipelines.
• Developers who want to learn a futuristic programming model for Big data processing.