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PostgreSQL Summary Stats and Window Functions

4.5+
38 reviews
Beginner

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

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4 Hours12 Videos44 Exercises52,174 Learners

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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.

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    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.

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  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.

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In the following tracks

Data Analyst in SQLSQL Fundamentals

Collaborators

Mona Khalil
Sumedh Panchadhar
Marianna Lamnina
Michel Semaan HeadshotMichel 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.
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Fernando Gonzalez Prada HeadshotFernando 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.
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Don’t just take our word for it

*4.5
from 38 reviews
74%
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  • Ayçıl Ö.
    5 days

    Great

  • Karamagi D.
    27 days

    It was so cool, it gave me a clearer picture of joins and sub queries. It should have actually been the first course in the track 😅

  • Sarah S.
    about 1 month

    Great course

  • Itanya C.
    2 months

    I enjoyed the course very much.

  • Abdeljalil A.
    3 months

    Great .the examples in the exercises are challenging but well chosen.

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"Great"

Ayçıl Ö.

"It was so cool, it gave me a clearer picture of joins and sub queries. It should have actually been the first course in the track 😅"

Karamagi D.

"Great course"

Sarah S.

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