Practice database normalization vocabulary: 1NF through BCNF, partial dependencies, denormalization for performance, third normal form, and normalization trade-offs.
0 / 5 completed
1 / 5
A table with a repeating group — multiple phone numbers in a single column — violates which normal form?
First Normal Form (1NF) requires that every column holds atomic (indivisible) values and that there are no repeating groups. Storing multiple phone numbers in one cell, or having columns Phone1/Phone2/Phone3, both violate 1NF.
2 / 5
The schema review notes: 'This table has a ___ dependency — the city column depends on zip code, not on the full key.'
A partial dependency occurs in a table with a composite primary key when a non-key column depends on only one part of that key. This violates 2NF. The fix is to move the partially dependent column to a separate table.
3 / 5
The architect says: 'We ___ the orders table for performance — we store customer name directly instead of joining.'
Denormalization deliberately introduces redundancy (e.g., storing customer name in the orders table) to improve read performance by avoiding JOINs. It trades data consistency risk for query speed.
4 / 5
The design document states: 'The schema is in ___ normal form — no transitive dependencies remain.'
Third Normal Form (3NF) requires that every non-key attribute depends directly on the primary key and not on any other non-key attribute. Removing transitive dependencies ensures this.
5 / 5
During a design discussion the team weighs normalization ___ off: full normalization means more JOINs and slower reads.
The normalization trade-off is the tension between data integrity (higher normalization eliminates redundancy and anomalies) and query performance (more joins slow down reads). Most production schemas are partially denormalized for this reason.