Analyze and Retrieve Information from Text Using Google Cloud Natural Language

Lab Steps

Signing In to Google Cloud Console
Starting a Google Cloud Shell
Creating the Bucket That Contains the Text to Analyze
Performing Entity Analysis
Performing Sentiment Analysis

Ready for the real environment experience?

Time Limit45m
star star star star star


Google Cloud Natural Language is a machine learning service that enables you to analyze and retrieve different kinds of information from text, or from a text document, uploaded to Cloud Storage. By using Google's pre-created machine learning models, you can extract information such as sentiments, entities, content classifications, and syntax. This way, you can carry out text analysis and retrieve all the entities in a piece of text, with related information, or understand the sentiment expressed by a piece of text. By using Google Cloud Natural Language, you will use the same machine learning models that Google uses for its search engine. This ensures the speed and reliability of the retrieved information. If you want more information on Cloud Natural Language, follow this link.

In this lab, you will use Cloud Natural Language to perform entity analysis and sentiment analysis.

Learning Objectives 

Upon completion of this lab you will be able to:

  • Perform text analysis to retrieve entities described in a document
  • Understand sentiments by analyzing a text document

Intended Audience

This lab is intended for:

  • Google Cloud Professional Data Engineer (PDE) candidates
  • Data Engineers who want to build machine learning solutions using Google's pre-defined models
  • Individuals who want to implement text analysis solutions


This lab has no prerequisites.

Environment before
Environment after

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.