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Joining Data in SQL

Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.

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4 Hours14 Videos47 Exercises20,570 Learners3950 XPData Analyst TrackSQL Fundamentals Track

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Course Description

Joining data is an essential skill which enables us to draw information from separate tables together into a single, meaningful set of results. Learn to supercharge your queries using table joins and relational set theory in this course on joining data.

In this course, you’ll learn how to:
✓ Work with more than one table in SQL
✓ Use inner joins, outer joins and cross joins
✓ Leverage set theory, including unions, intersect, and except clauses
✓ Create nested queries

Every step is accompanied by exercises and opportunities to apply the theory and grow your confidence in SQL.
  1. 1

    Introducing Inner Joins

    Free

    In this chapter, you’ll be introduced to the concept of joining tables and will explore all the ways you can enrich your queries using joins—beginning with inner joins.

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    The ins and outs of INNER JOIN
    50 xp
    Your first join
    100 xp
    Joining with aliased tables
    100 xp
    USING in action
    100 xp
    Defining relationships
    50 xp
    Relationships in our database
    100 xp
    Inspecting a relationship
    100 xp
    Multiple joins
    50 xp
    Joining multiple tables
    100 xp
    Checking multi-table joins
    100 xp
  2. 2

    Outer Joins, Cross Joins and Self Joins

    After familiarizing yourself with inner joins, you will come to grips with different kinds of outer joins. Next, you will learn about cross joins. Finally, you will learn about situations in which you might join a table with itself.

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  3. 3

    Set Theory for SQL Joins

    In this chapter, you will learn about using set theory operations in SQL, with an introduction to UNION, UNION ALL, INTERSECT, and EXCEPT clauses. You’ll explore the predominant ways in which set theory operations differ from join operations.

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In the following tracks

Data AnalystSQL Fundamentals

Collaborators

james-datacamp
James Chapman
amy-4121b590-cc52-442a-9779-03eb58089e08
Amy Peterson
izzyweber-9bc35945-95bd-423b-833e-40780c76586f
Izzy Weber

Prerequisites

Intermediate SQL
Maham Khan Headshot

Maham Khan

Senior Data Science Content Developer at DataCamp

Hi, I am a Data Scientist and Senior Content Developer at DataCamp, on a mission to make data skills accessible for everyone. Most recently, I've worked on creating toolkits and exploring experimental applications of data science for urban analytics, disaster risk management and climate change mitigation, at the World Bank. I have a background in Experimental Psychology and Philosophy from the University of Oxford, and Urban Data Science from NYU.
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