SQL for Data Analysis

Course overview

This course teaches practical SQL analysis using PostgreSQL syntax and behavior. Each chapter builds one core capability with clear outcomes, realistic tasks, and checkpoints that reflect work done in reporting and operational analytics.

Syllabus

1. 01

   SELECT, WHERE, and ORDER BY

   Write clear PostgreSQL queries that pick needed columns, filter rows by business rules, and sort results for reporting.

   →
2. 02

   Joins

   Combine PostgreSQL tables with INNER and LEFT JOINs while preserving row grain, missing records, and trustworthy cross-table business totals.

   →
3. 03

   GROUP BY and HAVING

   Aggregate PostgreSQL data into trustworthy metrics with grouped calculations and post-aggregate filters.

   →
4. 04

   Subqueries

   Use PostgreSQL subqueries for precise filtering, comparison, and existence checks when they are clearer than joins.

   →
5. 05

   CTEs

   Structure multi-step PostgreSQL analysis with common table expressions so logic is easier to review and test.

   →
6. 06

   Window Functions

   Apply PostgreSQL window functions to rank rows, compute running totals, and compare each row to group context.

   →
7. 07

   Date-Time Analysis

   Work safely with PostgreSQL dates, timestamps, intervals, and truncation for stable period reporting.

   →
8. 08

   Optimization Basics

   Improve PostgreSQL query speed with indexing, selective predicates, and plan inspection before risky rewrites.

   →
9. 09

   Data Modeling and Normalization

   Design PostgreSQL tables with keys and constraints that reduce duplication and preserve data quality.

   →
10. 10

    Transactions and ACID

    Use PostgreSQL transaction control to keep multi-step updates consistent when failures or concurrent writes occur.

    →