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Building Batch Data Pipelines on Google Cloud

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Duration

2h 23m

level

Beginner

Course Creator

Google Cloud

Last Updated

01-Sep-22

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data.

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Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
Author Name: Google Cloud
Author Description:
Google Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.

Table of Contents

  • Introduction
    1min
  • Introduction to Building Batch Data Pipelines
    21mins
  • Executing Spark on Dataproc
    47mins
  • Serverless Data Processing with Dataflow
    36mins
  • Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
    33mins
  • Course Summary
    3mins
  • Course Resources
    0mins

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Building Batch Data Pipelines on Google Cloud
Building Batch Data Pipelines on Google Cloud
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