Google Cloud Dataflow is a fully managed service for stream and batch data processing. It allows users to develop and execute a wide range of data processing patterns, including ETL, analytics, real-time computation, and more, using Apache Beam SDKs.
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About Google Cloud Dataflow
Google Cloud Dataflow was introduced in 2014 by Google as part of their cloud platform. It was created to provide a unified model for batch and stream data processing, leveraging the Apache Beam SDKs to simplify the development of complex data pipelines.
Strengths of Google Cloud Dataflow include its fully managed service, scalability, and support for both batch and stream processing. Weaknesses include potentially high costs and a steep learning curve for new users. Competitors include Apache Spark, Amazon Kinesis, and Microsoft Azure Stream Analytics.
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How to hire a Google Cloud Dataflow expert
A Google Cloud Dataflow expert must have skills in Apache Beam SDKs, Python or Java programming, cloud infrastructure management, data pipeline design, and proficiency with Google Cloud Platform services like BigQuery and Cloud Storage.
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