Combining and Filtering Data with PostgreSQL

This course will teach you how to use PostgreSQL to expand your queries to filter and combine data. Using SQL, you’ll learn how to join data from multiple tables, combine result sets, and use aggregate and window functions.
Course info
Level
Beginner
Updated
Aug 13, 2019
Duration
1h 58m
Table of contents
Course Overview
Working with String Functions
Aggregating Functions
Exploring Join Types
Introducing Set Theory
Implementing Subqueries
Simplifying Queries with Common Table Expressions
Limiting Results with Window Functions
Wrapping Up
Description
Course info
Level
Beginner
Updated
Aug 13, 2019
Duration
1h 58m
Description

In this course, Combining and Filtering Data with PostgreSQL, you will learn how to expand your queries to retrieve additional data and achieve your desired results. First, you will learn the fundamentals of data types and how to work with string functions. Next, you will discover aggregate functions and how to filter aggregate results. Then, you will explore how to use joins to retrieve data from multiple tables. Set theory and unions will also be used to combine multiple result sets. Subqueries and common table expressions are introduced to help conduct more sophisticated analyses using multiple filter criteria. Finally, you will figure out window functions and how to partition and analyze data. When you’re finished with this course, you will have the skills and knowledge of PostgreSQL necessary to begin writing more complex queries to analyze data from multiple sources.

About the author
About the author

Jason Browning is a data and analytics professional, and loves to solve complex business problems by using Tableau as a visualization tool and SQL to query complex data.

More from the author
Querying Data from PostgreSQL
Beginner
1h 29m
Mar 6, 2019
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone. My name is Jason Browning, and welcome to my course, Combining and Filtering Data with PostgreSQL. I am the Assistant Vice Provost for Institutional Effectiveness at Dixie State University in St. George, Utah. SQL can be used to access and analyze data from multiple sources and across multiple databases. In this course, we will explore how to use SQL to aggregate information, join disparate datasets, and perform more advanced analysis. Some of the major topics that we will cover include aggregating data. How do we perform calculations on large groups or data sets? Combining multiple tables. How do we connect and use related data across various tables? Applying set theory. How do we work with multiple result sets? Writing subqueries. How do we combine multiple queries to dynamically filter our data? And windowing functions. How do we use these powerful analytic functions to partition and analyze our data? By the end of this course, you'll have the ability to write subqueries and apply SQL functions to perform more advanced filtering and combinations. You will also know how to apply windowing and aggregate functions to perform calculations across your data. Although the course is based in Postgres, much of what you learn will be applicable to any relational database platform. This course uses SQL and the PostgreSQL environment to write queries and explore these functions. Before beginning the course, you should be familiar with basic SQL syntax, relational database structure, and the pgAdmin interface. To become more familiar with these concepts, feel free to check out my Pluralsight course, Querying Data with PostgreSQL. I hope you'll join me on this journey to learn how to combine and filter data with PostgreSQL in this course at Pluralsight.