Column descriptions in dbt

Introduction

Column descriptions help explain what each column in your data means. This makes your data easier to understand for everyone.

When you want to share your data model with teammates who are new to the project.

When you need to document what each column represents in a table or model.

When you want to improve data quality by making column purposes clear.

When you prepare data for reports or dashboards and want to add context.

When you maintain your data models over time and want to avoid confusion.

Syntax

dbt

columns:
  - name: column_name
    description: "Description of what this column means or contains."

Descriptions are added inside the model's YAML file under the columns section.

Each column has a name and a description field.

Examples

This describes the user_id column as a unique ID for users.

dbt

columns:
  - name: user_id
    description: "Unique identifier for each user."

This explains that order_date stores the date of an order.

dbt

columns:
  - name: order_date
    description: "Date when the order was placed."

This clarifies that total_amount is the order's price in dollars.

dbt

columns:
  - name: total_amount
    description: "Total price of the order in USD."

Sample Program

This YAML snippet shows how to add descriptions to columns in a dbt model named orders. Each column has a clear explanation to help users understand the data.

dbt

version: 2
models:
  - name: orders
    description: "Table containing customer orders."
    columns:
      - name: order_id
        description: "Unique ID for each order."
      - name: customer_id
        description: "ID of the customer who placed the order."
      - name: order_date
        description: "Date when the order was made."
      - name: total_amount
        description: "Total cost of the order in USD."

Important Notes

Descriptions appear in dbt documentation sites and help with data cataloging.

Keep descriptions short and clear for best results.

You can update descriptions anytime to keep documentation current.

Summary

Column descriptions explain what each column means.

They are added in the YAML file under the columns section.

Good descriptions make data easier to use and share.

Practice

1. What is the main purpose of adding column descriptions in dbt?

easy

A. To change the data type of columns

B. To create new columns in the model

C. To explain what each column means for better understanding

D. To write SQL queries inside the YAML file

Solution

1. Step 1: Understand the role of column descriptions

   Column descriptions provide explanations about what each column represents in the data model.

2. Step 2: Differentiate from other YAML uses

   They do not change data types, create columns, or contain SQL code; they only describe columns.

3. Final Answer:

   To explain what each column means for better understanding -> Option C

4. Quick Check:

   Column descriptions = explain columns [OK]

Hint: Descriptions explain columns, not change data or structure [OK]

Common Mistakes:

• Thinking descriptions change data types
• Confusing descriptions with SQL code
• Assuming descriptions create new columns

2. Which of the following is the correct syntax to add a column description in a dbt YAML file?

easy

A. description:
customer_id: 'Unique ID for each customer'

B. columns:
- name: customer_id
description: 'Unique ID for each customer'

C. columns:
customer_id: 'Unique ID for each customer'

D. columns:
- customer_id: 'Unique ID for each customer'

Solution

1. Step 1: Recall YAML structure for columns in dbt

   The correct format uses a list under columns: with each item having name and description keys.

2. Step 2: Compare options to correct format

   columns: - name: customer_id description: 'Unique ID for each customer' matches the correct YAML syntax with dash, name, and description keys properly indented.

3. Final Answer:

   columns: - name: customer_id description: 'Unique ID for each customer' -> Option B

4. Quick Check:

   YAML columns list with name and description = columns: - name: customer_id description: 'Unique ID for each customer' [OK]

Hint: Use dash list with name and description keys in YAML [OK]

Common Mistakes:

• Using key-value pairs without dash list
• Putting description outside columns section
• Incorrect indentation or missing name key

3. Given this YAML snippet in a dbt model:

columns:
  - name: order_id
    description: 'Unique order identifier'
  - name: order_date
    description: 'Date when order was placed'

What will dbt show for the order_date column in documentation?

medium

A. No description available

B. Unique order identifier

C. order_date

D. Date when order was placed

Solution

1. Step 1: Locate the description for order_date

   The YAML shows order_date has description 'Date when order was placed'.

2. Step 2: Understand dbt documentation behavior

   dbt uses the description text to show in docs, not the column name or other text.

3. Final Answer:

   Date when order was placed -> Option D

4. Quick Check:

   dbt docs show column description text [OK]

Hint: dbt docs show the description text, not column name [OK]

Common Mistakes:

• Confusing column name with description
• Assuming no description if present
• Picking wrong description text

4. You wrote this YAML for column descriptions but dbt docs shows no descriptions:

columns:
  - name: user_id
    description 'User unique ID'

What is the error causing descriptions not to appear?

medium

A. Missing colon after description key

B. Wrong indentation of columns

C. Missing dash before name

D. Description text should be uppercase

Solution

1. Step 1: Check YAML syntax for description key

   The line description 'User unique ID' is missing a colon after description.

2. Step 2: Understand YAML parsing impact

   Without the colon, YAML is invalid and dbt cannot read the description, so docs show no description.

3. Final Answer:

   Missing colon after description key -> Option A

4. Quick Check:

   YAML keys need colon after them [OK]

Hint: Always put colon after YAML keys like description [OK]

Common Mistakes:

• Forgetting colon after keys
• Incorrect indentation
• Assuming case sensitivity matters

5. You want to add descriptions for multiple columns in a dbt model YAML file. Which approach correctly documents two columns product_id and price with descriptions, ensuring dbt docs will display them properly?

hard

A. columns:
- name: product_id
description: 'ID of the product'
- name: price
description: 'Price in USD'

B. columns:
product_id: 'ID of the product'
price: 'Price in USD'

C. columns:
- product_id: 'ID of the product'
- price: 'Price in USD'

D. columns:
name: product_id
description: 'ID of the product'
name: price
description: 'Price in USD'

Solution

1. Step 1: Recall correct YAML list format for multiple columns

   Each column must be an item in a list with name and description keys.

2. Step 2: Evaluate each option's structure

   columns: - name: product_id description: 'ID of the product' - name: price description: 'Price in USD' correctly uses a list with two items, each having name and description properly indented.

3. Final Answer:

   columns: - name: product_id description: 'ID of the product' - name: price description: 'Price in USD' -> Option A

4. Quick Check:

   List of columns with name and description keys = columns: - name: product_id description: 'ID of the product' - name: price description: 'Price in USD' [OK]

Hint: Use dash list with name and description for each column [OK]

Common Mistakes:

• Using key-value pairs without dash list
• Repeating keys without list items
• Incorrect indentation breaking YAML