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Build and Optimize Data Warehouses with BigQuery

Fundamental Kroki: 7 7 godz. Punkty: 34

Earn a skill badge by completing the Build and Optimize Data Warehouses with BigQuery quest, where you will learn how to transform your data warehouse using BigQuery, including how to: 1. Use a command line interface to query and load sample data. 2. Create new reporting tables using SQL, JOINS, and UNIONs. 3. Create dataset partitions that will reduce cost and improve query performance. 4. Create and troubleshoot joins. 5. Load, query, and un-nest semi-structured datasets. 6. Use Data Catalog.

A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

Wymagania wstępne:

Prior to enrolling in this skill badge quest, it is recommended that you have a basic knowledge of SQL.

Quest Outline

Moduł

BigQuery: Qwik Start – wiersz poleceń

Z tego modułu praktycznego dowiesz się, jak tworzyć zapytania dotyczące tabel publicznych i wczytywać przykładowe dane w BigQuery przy użyciu interfejsu wiersza poleceń. Obejrzyj te krótkie filmy: Get Meaningful Insights with Google BigQuery (Zyskaj ważne dane dzięki Google BigQuery) i BigQuery: Qwik Start – Qwiklabs Preview (BigQuery: Qwik Start – omówienie z Qwiklabs).

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Moduł

Creating a Data Warehouse Through Joins and Unions

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

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Moduł

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.

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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.

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Moduł

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.

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Moduł

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.

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Moduł

Tworzenie i optymalizowanie hurtowni danych przy użyciu BigQuery: Challenge Lab

Ten Challenge Lab (moduł-wyzwanie) sprawdza Twoje umiejętności tworzenia i optymalizowania hurtowni danych przy użyciu BigQuery

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