Section 1 Review
You've finished Database Foundations, the first section of Database Testing. This page is a dedicated recap — bookmark it as a fast reference, separate from the modules themselves.
Section Summary
✔ What is Database Testing? — why a feature can pass every UI and API test while the underlying data is still wrong, and the specific question database testing answers that no interface-level test can
✔ Relational Database Fundamentals — tables, rows, columns, primary and foreign keys, and why "what else references this row" is the question a foreign key raises whenever data changes
✔ SQL for Testers — the core verification toolkit: SELECT, WHERE, ORDER BY, JOIN, GROUP BY, COUNT, SUM, EXISTS
How they build on each other: Module 1 established why the data layer needs direct verification. Module 2 gave you the vocabulary to reason about that data's structure — tables, keys, relationships. Module 3 turned that vocabulary into an actual, usable skill: queries that answer real verification questions, not just describe the schema.
Core SQL Verification Quick Reference
| Question You're Asking | Query Pattern |
|---|---|
| Did exactly one row get created (no duplicate)? | SELECT COUNT(*) ... WHERE ... GROUP BY |
| Does the total match what the feature claims? | SELECT SUM(column) ... WHERE ... |
| Is this field correctly empty? | WHERE column IS NULL (never = NULL) |
| Do two related tables agree? | JOIN on the foreign key |
| Did anything orphaned get left behind? | EXISTS or a JOIN checking for unmatched rows |
Section 1 Knowledge Check
Five realistic scenarios. For each, decide which SQL pattern (or combination) from this section you'd reach for, and why. No answers are provided here. Solutions: Section 1 Solutions.
Scenario 1: A customer reports seeing the same beneficiary listed twice after their connection dropped mid-save.
Scenario 2: You need to confirm that closing an AtlasBank account correctly cancelled every scheduled payment tied to it, with none left in a PROCESSING state.
Scenario 3: Finance needs confirmation that the total of all SUCCESS-status debit transactions for an account matches the amount the account's balance actually decreased by.
Scenario 4: A tester wants to confirm a newly closed account's closed_date field was actually set, and that it wasn't left blank by mistake.
Scenario 5: You need a list of every customer whose KYC status is VERIFIED, along with each of their account balances, in a single result.
Continue to Section 2
Data Validation, starting with CRUD Validation — where this section's SQL toolkit becomes a systematic framework for verifying Create, Read, Update, and Delete operations.