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BigQuery for Data Warehousing

Fundamental 8 个步骤 7 个小时 31 个积分

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.

Data

预备知识:

It is recommended but not required that students have a familiarity with data and spreadsheets.

Quest Outline

实操实验

BigQuery: Qwik Start - Command Line

This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
实操实验

Creating a Data Warehouse Through Joins and Unions

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

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
实操实验

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.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
实操实验

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.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
实操实验

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.

Deutsch English español (Latinoamérica) français 日本語 한국어 português (Brasil)
实操实验

Data Catalog: Qwik Start

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

实操实验

Exploring Dataset Metadata Between Projects with Data Catalog

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

实操实验

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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