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ETL Processing on Google Cloud Using Dataflow and BigQuery

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Checkpoints

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Create a Cloud Storage Bucket

Copy Files to Your Bucket

Create the BigQuery Dataset (name: lake)

Build a Data Ingestion Dataflow Pipeline

Build a Data Transformation Dataflow Pipeline

Build a Data Enrichment Dataflow Pipeline

Build a Data lake to Mart Dataflow Pipeline

ETL Processing on Google Cloud Using Dataflow and BigQuery

1시간 크레딧 7개

GSP290

Google Cloud Self-Paced Labs

Overview

In this lab you build several Data Pipelines that ingest data from a publicly available dataset into BigQuery, using these Google Cloud services:

  • Cloud Storage
  • Dataflow
  • BigQuery

You will create your own Data Pipeline, including the design considerations, as well as implementation details, to ensure that your prototype meets the requirements. Be sure to open the python files and read the comments when instructed to.

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  • Google Cloud Console에 대한 임시 액세스 권한을 얻습니다.
  • 초급부터 고급 수준까지 200여 개의 실습이 준비되어 있습니다.
  • 자신의 학습 속도에 맞춰 학습할 수 있도록 적은 분량으로 나누어져 있습니다.
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