Pipeline
Data engineering and database operations — SQL from table creation through complex joins, aggregations, constraints, and triggers.
Modules
| Module | Description | Files |
|---|
| Databases | SQL: DDL, CRUD, filtering, grouping, joins, constraints, triggers, schema design | 18 tasks + 4 schema dumps |
Learning Path
- Foundation (Tasks 0–1):
CREATE DATABASE, CREATE TABLE, data types
- CRUD Operations (Tasks 2–3):
SELECT *, INSERT INTO
- Filtering & Sorting (Tasks 4–7):
WHERE, ORDER BY, GROUP BY, AVG, MAX
- Joins (Tasks 8–12):
INNER JOIN, LEFT JOIN, chained joins, COUNT, SUM
- Constraints (Tasks 13–14):
AUTO_INCREMENT, NOT NULL, UNIQUE, PRIMARY KEY, ENUM
- Real-World Data (Tasks 15–16):
LIKE, COALESCE, arithmetic in SELECT
- Automation (Tasks 17–18):
CREATE TRIGGER, BEFORE/AFTER, OLD/NEW references
Schema Datasets
| File | Contents |
|---|
hbtn_0d_tvshows.sql | TV shows + genres (many-to-many via junction table) |
hbtn_0d_tvshows_rate.sql | Extended with ratings fact table |
metal_bands.sql | Metal bands dataset with origin, fans, lifespan |
temperatures.sql | Weather time-series by city, state, year, month |
Resources