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Views in PostgreSQL

BeginnerGuided Project

In this project, you will learn how to create and execute views and materialized views in the PostgreSQL database service using the pgAdmin graphical user interface (GUI) tool.

Language

  • English

Topic

  • Computer Science & Information Technology

Enrollment Count

  • 1.03K

Skills You Will Learn

  • PostgreSQL, Relation, Databases

Offered By

  • IBM

Estimated Effort

  • 25 minutes

Platform

  • SkillsNetwork

Last Update

  • October 30, 2025
About this Guided Project

About This Guided Project

In this project, you will learn how to create and execute views and materialized views in the PostgreSQL database service using the pgAdmin graphical user interface (GUI) tool. Materialized views behave differently compared to regular views. In materialized views, result set is materialized or saved for future use. You can't insert, update, or delete rows like in regular views. Materialized views can improve performance.



Objectives

After completing this project, you will be able to use pgAdmin with PostgreSQL to:
  • Restore a database schema and data
  • Create and execute a view
  • Create and execute a materialized view

Requirements

To complete this project you will need the PostgreSQL relational database service which will be available as part of the IBM Skills Network Labs (SN Labs) Cloud IDE. SN Labs is a virtual lab environment used in this project


Frequently Asked Questions

Do I need to install any software to participate in this project?


Everything you need to complete this project will be provided to you via the Skills Network Labs and it will all be available via a standard web browser.



What web browser should I use?


The Skills Network Labs platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.


Instructors

Sandip Saha Joy

Cognitive Data Scientist

An aspiring data scientist who enjoys connecting the dots: be it ideas from different disciplines, people from different teams, or applications from different industries. Have an academic background in computing science and strong technical skills in computer vision, machine learning and data science.

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