Building Batch Data Pipelines on GCP

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 Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.
Course info
Rating
(13)
Level
Intermediate
Updated
Jan 14, 2020
Duration
2h 42m
Table of contents
Introduction
Introduction to Batch Data Pipelines
Executing Spark on Cloud Dataproc
Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
Serverless Data Processing with Cloud Dataflow
Summary
Description
Course info
Rating
(13)
Level
Intermediate
Updated
Jan 14, 2020
Duration
2h 42m
Description

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 Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.

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About the author

Build, innovate, and scale with Google Cloud Platform.

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