Skip to main content

PostgreSQL Summary Stats and Window Functions

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

Start Course for Free
4 Hours12 Videos44 Exercises37,735 Learners3550 XPData Analyst TrackSQL Fundamentals Track

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies


Course Description

Have you ever wondered how data professionals use SQL to solve real-world business problems, like generating rankings, calculating moving averages and running totals, deduplicating data, or performing time intelligence? If you already know how to select, filter, order, join and group data with SQL, this course is your next step. By the end, you will be writing queries like a pro! You will learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon! Using flights data, you will discover how simple it is to use window functions, and how flexible and efficient they are.

  1. 1

    Introduction to window functions

    Free

    In this chapter, you'll learn what window functions are, and the two basic window function subclauses, ORDER BY and PARTITION BY.

    Play Chapter Now
    Introduction
    50 xp
    Window functions vs GROUP BY
    50 xp
    Numbering rows
    100 xp
    Numbering Olympic games in ascending order
    100 xp
    ORDER BY
    50 xp
    Numbering Olympic games in descending order
    100 xp
    Numbering Olympic athletes by medals earned
    100 xp
    Reigning weightlifting champions
    100 xp
    PARTITION BY
    50 xp
    Reigning champions by gender
    100 xp
    Reigning champions by gender and event
    100 xp
    Row numbers with partitioning
    50 xp
  2. 2

    Fetching, ranking, and paging

    In this chapter, you'll learn three practical applications of window functions: fetching values from different parts of the table, ranking rows according to their values, and binning rows into different tables.

    Play Chapter Now
  3. 4

    Beyond window functions

    In this last chapter, you'll learn some techniques and functions that are useful when used together with window functions.

    Play Chapter Now

In the following tracks

Data AnalystSQL Fundamentals

Collaborators

sumedhpanchadhar
Sumedh Panchadhar
mona-kay
Mona Khalil
ml3648
Marianna Lamnina
Fernando Gonzalez Prada Headshot

Fernando Gonzalez Prada

Data Science Consultant

Fernando is a data science professional with over 20 years of experience in databases, data integration, machine learning, and business intelligence. He designs analytics solutions with Microsoft Data Platform technologies and open source products. He has degrees in economics and IT certifications and is studying Business Analytics at Columbia University. Fernando loves teaching data science to beginners and helping experienced professionals who are transitioning to data science.
See More
Michel Semaan Headshot

Michel Semaan

Data Scientist

Michel is a data scientist who's worked at leading Middle-Eastern startups like Bookwitty (e-commerce) and Anghami (music streaming). He loves using open-source technologies like Python, R, and SQL to analyze data, optimize KPIs, and solve problems.
See More

What do other learners have to say?

Join over 10 million learners and start PostgreSQL Summary Stats and Window Functions today!

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.