Configuring sources in YAML in dbt - Visual Walkthrough

Concept Flow - Configuring sources in YAML

Start YAML file

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Define 'sources' key

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Add source name

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Add tables under source

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Specify table details (name, description)

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Save YAML

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dbt reads source config

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Sources available for models

This flow shows how to write a YAML file to define data sources and tables for dbt to use in models.

Execution Sample

dbt

sources:
  - name: raw_data
    tables:
      - name: users
        description: 'User data from app'

Defines a source named 'raw_data' with a table 'users' and a description.

Execution Table

Step	YAML Line	Action	State Change	Result
1	sources:	Start defining sources	Create 'sources' key	Empty list for sources
2	- name: raw_data	Add source name	Append source dict with name 'raw_data'	sources = [{'name': 'raw_data'}]
3	tables:	Add tables key	Add empty 'tables' list to source	sources[0]['tables'] = []
4	- name: users	Add table name	Append table dict with name 'users'	sources[0]['tables'] = [{'name': 'users'}]
5	description: 'User data from app'	Add description	Add description to table dict	sources[0]['tables'][0]['description'] = 'User data from app'
6	End of YAML	Finish parsing	YAML fully parsed	Source config ready for dbt

💡 Reached end of YAML file, source configuration complete.

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 5	Final
sources	undefined	[{'name': 'raw_data'}]	[{'name': 'raw_data', 'tables': []}]	[{'name': 'raw_data', 'tables': [{'name': 'users'}]}]	[{'name': 'raw_data', 'tables': [{'name': 'users', 'description': 'User data from app'}]}]	[{'name': 'raw_data', 'tables': [{'name': 'users', 'description': 'User data from app'}]}]

Key Moments - 2 Insights

Why do we indent 'tables' under the source name?

Because YAML uses indentation to show hierarchy. 'tables' belongs to the source 'raw_data', so it must be indented under it as shown in step 3 of the execution table.

What happens if we forget to add a description for a table?

The table will still be recognized by dbt, but it won't have a description metadata. Step 5 shows adding description is optional but helpful.

Visual Quiz - 3 Questions

Look at the execution table, what is the state of 'sources' after step 4?

A [{'name': 'raw_data', 'tables': []}]

B [{'name': 'raw_data', 'tables': [{'name': 'users'}]}]

C [{'name': 'raw_data'}]

D undefined

💡 Hint

Check the 'State Change' column at step 4 in the execution table.

At which step is the table description added?

A Step 3

B Step 2

C Step 5

D Step 6

💡 Hint

Look for the 'Add description' action in the execution table.

If we remove the 'tables' key, what would happen to the source configuration?

A dbt will have no tables under the source, so no tables to reference.

B The source will be invalid and cause an error.

C The source will automatically add default tables.

D The source will be ignored completely.

💡 Hint

Think about the role of 'tables' in the variable_tracker and execution_table.

Concept Snapshot

Configuring sources in YAML for dbt:
- Use 'sources:' at top level
- Define each source with '- name:'
- Under each source, add 'tables:' list
- Each table has '- name:' and optional 'description:'
- Indentation shows hierarchy
- dbt reads this to know where data comes from

Full Transcript

This visual execution shows how to configure sources in YAML for dbt. We start by creating a 'sources' key, then add a source name. Under that source, we add a 'tables' list. Each table has a name and can have a description. Indentation is important to show the structure. The execution table traces each step of parsing the YAML lines and how the internal data structure changes. The variable tracker shows how the 'sources' variable builds up step by step. Key moments clarify why indentation matters and the role of descriptions. The quiz tests understanding of the state after steps and the effect of missing keys. This helps beginners see exactly how dbt reads source configs from YAML.