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ETL Processing on Google Cloud Using Dataflow and BigQuery

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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

1 hour 7 Credits

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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