Level 2: Aggregation & Joins (Combining Source Data) · Learn SQL | CodeSparring

Module 2.1: Aggregation and Grouping

Collapse rows into metrics: the aggregate functions, GROUP BY for per-category rollups, and HAVING to filter groups.

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Lesson 01Up next

Aggregate Functions

Collapse many rows into a single measure: the atom of every metric.

easy20 minStart

GROUP BY

Compute one metric row per category: the shape of a mart.

HAVING: Filtering Groups

Filter on aggregated values, not raw rows.

Module 2.2: Joining Tables

Combine source tables: inner joins on keys, LEFT joins that preserve rows, anti-joins for gaps, and self/outer joins.

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INNER JOIN and Join Keys

Combine two source tables on a matching key.

LEFT JOIN and Preserving Rows

Keep all rows from the driving table even when the match is missing.

Anti-Joins: Finding Missing Matches

Find records that have no counterpart: the DE's referential-integrity check.

Self-Joins and RIGHT/FULL OUTER

Join a table to itself and reconcile two sources with outer joins.

Module 2.3: Set Operations and Subqueries

Stack and compare result sets with UNION/INTERSECT/EXCEPT, and nest queries as scalar, IN, and correlated subqueries.

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UNION, INTERSECT, EXCEPT

Stack and compare result sets with set logic.

Subqueries: Scalar, IN, and Correlated

Nest a query inside another to filter or compute against a derived value.

Module 2.4: Readability and Conditional Logic

Make complex SQL legible with CTEs, and branch per-row with CASE expressions.

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CTEs: Readable Multi-Step Queries

Name subqueries with WITH so a transform reads top-to-bottom.

CASE: Conditional Columns

Branch a value inside a query for bucketing and pivoting.