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Data Engineering

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Data Engineering

7 个小时 Advanced universal_currency_alt 42 个积分
This advanced-level quest is unique amongst the other Qwiklabs 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 & Tensorflow, 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.

完成此课程中的所有活动即可赢取一枚徽章。完成挑战任务、游戏和课程即可收集 Qwiklabs 中的徽章。集齐所有徽章,彰显您的技能!

  • 实验

    Creating a Data Transformation Pipeline with Cloud Dataprep

    Cloud Dataprep by Trifacta 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

    Building an IoT Analytics Pipeline on Google Cloud

    This lab shows you how to connect and manage devices using Cloud IoT Core; ingest the stream of information using Cloud Pub/Sub; process the IoT data using Cloud Dataflow; use BigQuery to analyze the IoT data. Watch this short video, Easily Build an IoT Analytics 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

    Predict Visitor Purchases with a Classification Model in BQML

    In this lab you will use a newly available ecommerce dataset to run some typical queries that businesses would want to know about their customers’ purchasing habits.

  • 实验

    Predict Housing Prices with Tensorflow and AI Platform

    In this lab you will build an end to end machine learning solution using Tensorflow + AI Platform and leverage the cloud for distributed training and online prediction.

  • 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 bucktes in the US to buckets in Europe, then import th0se tables to a BigQuery dataset in Europe.

  • info
    Quest Info
    Prerequisites
    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.