Denormalization and when to use it in SQL - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is denormalization in databases?

Denormalization is the process of adding redundant data to a database to reduce the number of joins and improve read performance.

beginner

Why would you use denormalization?

You use denormalization to speed up data retrieval when read performance is more important than write performance or storage efficiency.

intermediate

What is a common downside of denormalization?

Denormalization can cause data inconsistency because the same data is stored in multiple places and must be kept in sync.

intermediate

Give an example of when denormalization is useful.

Denormalization is useful in reporting databases where fast read queries are needed and data changes less often.

intermediate

How does denormalization affect database writes?

Denormalization usually makes writes slower and more complex because multiple copies of data must be updated.

What is the main goal of denormalization?

A Increase write speed

B Reduce data redundancy

C Simplify database design

D Improve read query speed

Denormalization adds redundant data to speed up read queries, not to reduce redundancy or simplify design.

Which problem can denormalization cause?

A Data inconsistency

B Faster writes

C Less storage used

D Simpler queries

Denormalization can cause data inconsistency because the same data is stored in multiple places.

When is denormalization most useful?

A When storage space is limited

B When write performance is critical

C When read performance is critical

D When data changes very frequently

Denormalization is best when fast reads are needed, even if writes become slower.

Denormalization typically involves:

A Removing duplicate data

B Adding redundant data

C Splitting tables into smaller ones

D Encrypting data

Denormalization means adding redundant data to reduce joins and speed up queries.

Which is a trade-off of denormalization?

A Slower writes but faster reads

B Faster writes but slower reads

C Less data redundancy

D Simpler data updates

Denormalization speeds up reads but makes writes slower and more complex.

Explain what denormalization is and why you might use it in a database.

Think about how adding repeated data can make reading faster but updating harder.

Describe a scenario where denormalization would be a good choice and why.

Consider reporting or analytics systems that read a lot but update rarely.