Structured Query Language (SQL) - Part 2
The chapter focuses on advanced SQL queries, introducing aggregate functions and techniques for summarizing and manipulating data across multiple tables. It covers the use of the GROUP BY clause for categorizing data, the HAVING clause for filtering grouped results, various JOIN operations for combining data from related tables, subqueries for handling complex queries, and set operations for merging result sets. This module equips learners with essential tools to efficiently analyze and retrieve useful insights from comprehensive datasets.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- Aggregate functions summarize large datasets into single values.
- The GROUP BY clause categorizes data, and the HAVING clause filters grouped results.
- SQL JOINs combine data from different tables based on relationships.
- Subqueries enable complex querying by nesting SELECT statements.
- Set operations allow for combining and comparing results from multiple queries.
Key Concepts
- -- Aggregate Functions
- Functions like COUNT, SUM, AVG, MIN, and MAX that summarize data across multiple rows into single values.
- -- GROUP BY Clause
- A SQL clause that groups rows sharing a specified column value, allowing for aggregate functions to be applied on each group.
- -- HAVING Clause
- A SQL clause used to filter results after aggregation based on conditions involving aggregate functions.
- -- SQL JOIN
- An operation that combines rows from two or more tables based on a related column between them.
- -- Subqueries
- A nested SQL query used to retrieve data that will be used in the main query.
- -- Set Operations
- Operations like UNION, INTERSECT, and EXCEPT that combine results from two or more SELECT statements.
Additional Learning Materials
Supplementary resources to enhance your learning experience.