Seeds for static reference data in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a seed in dbt?

A seed in dbt is a CSV file that contains static reference data. It is loaded into the data warehouse as a table for easy use in transformations.

beginner

Why use seeds for static reference data in dbt?

Seeds allow you to manage small, unchanging datasets like country codes or product categories directly in your project, making them easy to version control and use in models.

beginner

How do you load a seed file into your data warehouse using dbt?

You run the command dbt seed. This reads CSV files in the seeds folder and creates tables in your warehouse.

beginner

Where do you place seed CSV files in a dbt project?

Seed CSV files are placed in the seeds/ directory inside your dbt project folder.

intermediate

Can you transform seed data directly in dbt models?

Yes, once seeds are loaded as tables, you can reference and transform them in your dbt models like any other table.

What command do you use to load seed files into your warehouse in dbt?

A dbt seed

B dbt run

C dbt test

D dbt compile

The dbt seed command loads CSV files from the seeds folder into your data warehouse as tables.

Where should you store static reference data CSV files in a dbt project?

A seeds/

B models/

C snapshots/

D macros/

Seed CSV files belong in the seeds/ directory to be recognized by dbt.

What is a key benefit of using seeds for static data?

A They run faster than models

B They automatically update from external sources

C They replace all models

D They allow version control of static data

Seeds let you keep static data in your project files, so you can track changes with version control.

Can you join seed tables with other tables in dbt models?

A No, seeds are read-only

B Yes, seeds become regular tables after loading

C Only if you convert seeds to models

D Only in snapshots

Once loaded, seed data is a normal table and can be joined or transformed like any other table.

Which of these is NOT true about seeds in dbt?

A Seeds are stored as CSV files

B Seeds can be used for static reference data

C Seeds automatically update from APIs

D Seeds are loaded with dbt seed command

Seeds do not update automatically from APIs; they are static files you manage manually.

Explain what seeds are in dbt and why they are useful for static reference data.

Think about how you keep small, unchanging data in your project.

Describe the steps to add and use a seed file in a dbt project.

Consider the file location, command, and usage in models.