Structure and Analyze Data with Google BigQuery

The hands-on lab is part of these learning paths

Google BigQuery
course-steps 3 certification 1 lab-steps 1 quiz-steps 1

Lab Steps

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Signing In to Google Cloud Console
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Google BigQuery Core Concepts Overview
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Creating a BigQuery Dataset
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Importing a BigQuery Table
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Composing a BigQuery Query
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Validate Getting Started with Google BigQuery

Ready for the real environment experience?

DifficultyBeginner
Max Duration35m
Students57
Ratings
5/5
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Description

Google BigQuery is a serverless, high-scalable and fully-managed database service which allows you to handle and query a big amount of data in a very short time. BigQuery is designed to make data analysts more productive with unmatched price-performance. Because there is no infrastructure to manage, you can focus on uncovering meaningful insights using familiar SQL without the need for a database administrator. BigQuery is compatible with a lot of GCP's services, such as Cloud Datalab, that allow the user to represents data in an innovative way. This Lab will show you the basic concepts of BigQuery and will allow you to handle data and query them in a real GCP environment.

Learning Objectives

Upon completion of this Lab you will be able to:

  • Understand the key concepts of Google BigQuery
  • Explain what Datasets and Tables represent
  • Perform queries on data inside Google BigQuery

Intended Audience

This Lab is intended for:

  • Google Cloud Associate Cloud Engineer (ACE) certification candidates
  • Individuals that are familiar with SQL and databases who want to deep know big data solutions
  • Solutions architects who want to build smart, efficient and responsive data infrastructures

Prerequisites

Basic knowledge of SQL and structured queries is a plus but it is not required.

Environment before
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Environment after
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About the Author

Stefano studies Computer Science and is passionate about technology. He loves working with Cloud services and learning all the best practices for them. Amazon Web Services is the provider he prefers and Node.js the programming language he always uses to code. When he's not involved in studying or working, Stefano loves riding his motorbike and exploring new places.