[Solved] You have a large dataset that updates daily with new and changed rows.... Which materialization strategy should you choose in dbt? | dbt

dbt - Performance Optimization

You have a large dataset that updates daily with new and changed rows. You want fast query performance and to avoid rebuilding the entire table each time. Which materialization strategy should you choose in dbt?

AUse <code>incremental</code> materialization to add and update rows efficiently.

BUse <code>table</code> materialization and rebuild daily.

CUse <code>view</code> materialization for real-time data.

DUse <code>ephemeral</code> materialization to avoid creating tables.

Step-by-Step Solution

Solution:

Step 1: Analyze dataset size and update pattern
The dataset is large and updates daily with new and changed rows, so full rebuilds are costly.
Step 2: Match materialization to needs
incremental materialization updates only new or changed rows, improving performance and avoiding full rebuilds.
Final Answer:
Use incremental materialization to add and update rows efficiently. -> Option A
Quick Check:
Incremental = efficient updates for large, changing data [OK]

Quick Trick: Incremental suits large, frequently updated datasets [OK]

Common Mistakes:

MISTAKES

Choosing view which rebuilds every query
Using table and rebuilding fully each time
Using ephemeral which does not create tables

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Which materialization strategy should you choose in dbt?

Step 1: Analyze dataset size and update pattern

Step 2: Match materialization to needs

Final Answer:

Quick Check:

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