Loading CSV seeds in dbt - Step-by-Step Execution

Concept Flow - Loading CSV seeds

Place CSV file in 'seeds/' folder

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Run 'dbt seed' command

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dbt reads CSV file

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dbt creates table in warehouse

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Table ready for use in models

This flow shows how dbt loads CSV seed files into your data warehouse as tables for use in your projects.

Execution Sample

dbt

dbt seed
-- loads CSV files from 'seeds/' folder into warehouse tables

This command reads CSV seed files and creates tables in your data warehouse.

Execution Table

Step	Action	Input	Output	Notes
1	Locate CSV file	'seeds/customers.csv'	File found	CSV file must be in 'seeds/' folder
2	Run command	dbt seed	Command starts	dbt begins processing seed files
3	Read CSV	'customers.csv'	CSV content loaded	dbt parses CSV rows and columns
4	Create table	CSV content	Table 'customers' created	Table schema inferred from CSV headers
5	Finish	Table created	Seed loading complete	Table ready for use in dbt models
6	Exit	All seeds processed	Process ends	No more CSV files to load

💡 All CSV seed files processed and tables created in warehouse

Variable Tracker

Variable	Start	After Step 3	After Step 4	Final
CSV file path	None	'seeds/customers.csv'	'seeds/customers.csv'	'seeds/customers.csv'
CSV content	None	Loaded rows and columns	Loaded rows and columns	Loaded rows and columns
Warehouse table	None	None	Table 'customers' created	Table 'customers' created

Key Moments - 3 Insights

Why must the CSV file be placed in the 'seeds/' folder?

dbt only looks for seed files inside the 'seeds/' folder when running 'dbt seed', so placing files elsewhere means they won't be loaded (see execution_table step 1).

How does dbt know the table schema from the CSV?

dbt reads the CSV header row to infer column names and types automatically during the read CSV step (execution_table step 3).

What happens if you run 'dbt seed' with no CSV files in 'seeds/'?

dbt runs but finds no files to load, so no tables are created and the process ends quickly (implied by exit_note).

Visual Quiz - 3 Questions

Look at the execution table, what is the output after step 4?

A Table 'customers' created

B CSV content loaded

C File found

D Seed loading complete

💡 Hint

Check the 'Output' column for step 4 in the execution_table.

At which step does dbt read the CSV file content?

A Step 4

B Step 2

C Step 3

D Step 5

💡 Hint

Look for the step where 'CSV content loaded' appears in the Output column.

If the CSV file is not in the 'seeds/' folder, what will happen when running 'dbt seed'?

A dbt will create an empty table

B dbt will not find the file and skip loading

C dbt will load the file anyway

D dbt will throw an error and stop

💡 Hint

Refer to key_moments about file location and execution_table step 1.

Concept Snapshot

Loading CSV seeds in dbt:
- Place CSV files in 'seeds/' folder
- Run 'dbt seed' command
- dbt reads CSV headers and data
- Creates tables in your warehouse
- Tables are ready for use in models

Full Transcript

Loading CSV seeds in dbt means putting your CSV files inside the 'seeds/' folder of your project. When you run the command 'dbt seed', dbt looks inside this folder, reads each CSV file, and creates a table in your data warehouse with the same name as the file. The table columns come from the CSV headers. This process lets you use static data easily in your dbt models. If the CSV file is not in the 'seeds/' folder, dbt will not find it and will skip loading it. After loading, the tables are ready to be queried or joined in your transformations.