Google Cloud Skills Boost

Data Engineering

4 个小时 Intermediate universal_currency_alt 15 积分
This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
Data Engineering徽章


  • 实验

    Creating a Data Transformation Pipeline with Cloud Dataprep

    Cloud Dataprep by Alteryx is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis. In this lab you will explore the Cloud Dataprep UI to build a data transformation pipeline.

  • 实验

    ETL Processing on Google Cloud Using Dataflow and BigQuery

    In this lab you will build several Data Pipelines that will ingest data from a publicly available dataset into BigQuery.

  • 实验

    Cloud Composer: Copying BigQuery Tables Across Different Locations

    In this advanced lab you will create and run an Apache Airflow workflow in Cloud Composer that exports tables from a BigQuery dataset located in Cloud Storage buckets in the US to buckets in Europe, then import th0se tables to a BigQuery dataset in Europe.

  • info
    This quest requires proficiency with Google Cloud Services, particularly those relating to working with large datasets. It is recommended that the student have at least earned a Badge by completing the hands-on labs in the Baseline: Data, ML, and AI and/or the Google Cloud Essentials quests before beginning. Additional lab experience with the Scientific Data Processing and the Machine Learning APIs Quests will be useful.
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