Google Cloud Skills Boost

BigQuery for Data Warehousing

6 ore Introduttivi universal_currency_alt 5 crediti
Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. 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 this quest to receive an exclusive Google Cloud digital badge.
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  • Lab

    BigQuery: Qwik Start - Command Line

    Questo lab pratico illustra come eseguire query su tabelle pubbliche e caricare dati di esempio in BigQuery utilizzando l'interfaccia a riga di comando. Guarda questi brevi video: Get Meaningful Insights with Google BigQuery e BigQuery: Qwik Start - Qwiklabs Preview.

  • Lab

    Creating a Data Warehouse Through Joins and Unions

    This lab focuses on how to create new reporting tables using SQL JOINS and UNIONs.

  • Lab

    Creating Date-Partitioned Tables in BigQuery

    This lab focuses on how to query partitioned datasets and how to create your own dataset partitions to improve query performance, which reduces cost.

  • Lab

    Troubleshooting and Solving Data Join Pitfalls

    This lab focuses on how to reverse-engineer the relationships between data tables and the pitfalls to avoid when joining them together.

  • Lab

    Working with JSON, Arrays, and Structs in BigQuery

    In this lab you will work with semi-structured data (ingesting JSON, Array data types) inside of BigQuery. You will practice loading, querying, troubleshooting, and unnesting various semi-structured datasets.

  • Lab

    Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors

    In this lab you will explore existing datasets with Data Catalog and mine the table and column metadata for insights.

  • info
    Informazioni Quest
    Prerequisiti
    It is recommended but not required that students have a familiarity with data and spreadsheets.
    Lingue disponibili
    English, français, español (Latinoamérica), 日本語, português (Brasil) e Deutsch
    Cosa faccio al termine della Quest?
    Al termine della Quest, puoi esplorare contenuti aggiuntivi nel tuo percorso di apprendimento o esplorare il catalogo formativo.
    Quali badge posso guadagnare?
    Al termine di una Quest, guadagnerai un badge di completamento. Alcune Quest mettono alla prova la tua capacità di applicare le tue conoscenze tramite un Challenge Lab finale di valutazione. Per le Quest di questo tipo, riceverai un badge delle competenze. I badge possono essere visualizzati sul tuo profilo e condivisi sul tuo social network.