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.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] Hi, everyone. My name is Jason Browning and welcome to my course. Combining and filtering data with Post Grads Sequel I am the assistant vice provost for institutional effectiveness at Dixie State University in St George, Utah. Sequel could be used to access an analyze data from multiple sources and across multiple databases. In this course, we will explore how to use sequel to aggregate information, joined the spirit data sets and perform or 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 results? Sets writing sub queries 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 sub queries and apply sequel functions to perform or advanced filtering and combinations. You will also know howto windowing aggregate functions to form calculations across your data. Although the course is based in post grads. Much of what you learned will be applicable to any relational database platform. This course uses Sequel and the Post Grads sequel environment to write queries and explore these functions before beginning the course. You should be familiar with basic sequel syntax, relational database structure and the PG admin interface. To become more familiar with these concepts, feel free to check out my parole site course Clearing Data with Post Grads Sequel I hope you'll join me on this journey to learn how to combine and filter data with Post Grads sequel in this course at plural site.