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Google Cloud Dataflow

Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines to process data in both batch and streaming modes. It provides a serverless environment that automatically handles resource provisioning, scaling, and optimization, allowing developers to focus on writing data processing logic. It integrates seamlessly with other Google Cloud services like BigQuery, Pub/Sub, and Cloud Storage for building end-to-end data pipelines.

Also known as: Dataflow, GCP Dataflow, Cloud Dataflow, Google Dataflow, Apache Beam on GCP
🧊Why learn Google Cloud Dataflow?

Developers should use Google Cloud Dataflow when building scalable, real-time data processing pipelines that require unified batch and stream processing, such as ETL jobs, real-time analytics, or event-driven applications. It's particularly valuable in scenarios where automatic scaling, minimal operational overhead, and tight integration with the Google Cloud ecosystem are priorities, such as processing IoT data streams or transforming large datasets for machine learning.

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