In ERP contexts, what is a trade-off between normalization and denormalization?

• A. They speed up lookups and range queries but slow inserts/updates and consume storage.
• B. They never affect performance.
• C. They reduce storage requirements.
• D. They speed up writes.

Answer: (A)

The main idea here is how duplicating data affects performance. Denormalizing data means you store some information in more than one place so reads don’t have to join many tables. That makes lookups and range queries much faster, which is especially helpful in ERP scenarios with big reports and dashboards. But keeping those duplicates in sync costs storage space, and any insert or update has to update multiple places, which can slow down writes. So the trade-off is faster reads at the expense of more storage and slower writes.

The other options don’t fit because performance isn’t zeroed out by normalization, normalization usually reduces storage rather than increases it, and denormalization typically slows down writes rather than speeding them up.