Why documentation makes data discoverable in dbt

Introduction

Documentation helps people find and understand data easily. It explains what data means and how to use it.

When you want your team to quickly find the right data for reports.

When new team members need to learn about data sources fast.

When you want to avoid confusion about data definitions.

When you want to keep track of changes in data over time.

When you want to share data knowledge across different departments.

Syntax

dbt

models:
  - name: model_name
    description: "A clear explanation of the data model"
    columns:
      - name: column_name
        description: "What this column means and how to use it"

Documentation is written in YAML format in files like schema.yml.

Descriptions help users understand the purpose of tables and columns.

Examples

This example documents a model named 'customers' and its column 'customer_id'.

dbt

version: 2
models:
  - name: customers
    description: "Contains customer information like name and email"
    columns:
      - name: customer_id
        description: "Unique ID for each customer"

This documents the 'orders' model and explains the 'order_date' column.

dbt

version: 2
models:
  - name: orders
    description: "Details of customer orders"
    columns:
      - name: order_date
        description: "Date when the order was placed"

Sample Program

This sample shows how to document a 'sales' model with descriptions for the model and its columns.

dbt

version: 2
models:
  - name: sales
    description: "Sales data including product and revenue"
    columns:
      - name: product_id
        description: "ID of the product sold"
      - name: revenue
        description: "Revenue generated from the sale"

# This YAML file helps dbt generate documentation that makes sales data easy to find and understand.

Important Notes

Good documentation saves time by reducing questions about data meaning.

Keep descriptions clear and simple for everyone to understand.

Update documentation whenever data models change to keep it accurate.

Summary

Documentation explains data so people can find and use it easily.

It is written in YAML inside dbt model files.

Clear descriptions help everyone understand data purpose and usage.

Practice

1. Why is documentation important in dbt projects for data discoverability?

easy

A. It speeds up the data processing time.

B. It explains data clearly so users can find and understand it easily.

C. It automatically fixes errors in data models.

D. It encrypts data for security.

Solution

1. Step 1: Understand the purpose of documentation in dbt

   Documentation provides clear explanations about data models and columns.

2. Step 2: Connect documentation to data discoverability

   Clear explanations help users find and understand data easily, improving discoverability.

3. Final Answer:

   It explains data clearly so users can find and understand it easily. -> Option B

4. Quick Check:

   Documentation improves discoverability [OK]

Hint: Documentation means clear explanations for easy data finding [OK]

Common Mistakes:

• Confusing documentation with data processing speed
• Thinking documentation fixes data errors automatically
• Assuming documentation encrypts data

2. Which of the following is the correct way to add a description to a dbt model in YAML?

easy

A. models:
- name: sales
description: 'Contains sales data by region'

B. models:
name: sales
description: 'Contains sales data by region'

C. model:
- name: sales
description: 'Contains sales data by region'

D. models:
- sales:
description: 'Contains sales data by region'

Solution

1. Step 1: Recall YAML structure for dbt model descriptions

   The correct syntax uses 'models:' followed by a list with '- name:' and 'description:' keys.

2. Step 2: Identify the option matching this structure

   models: - name: sales description: 'Contains sales data by region' correctly uses a list item with 'name' and 'description' under 'models'.

3. Final Answer:

   models:\n - name: sales\n description: 'Contains sales data by region' -> Option A

4. Quick Check:

   Correct YAML list syntax [OK]

Hint: YAML lists use dash and indentation for model descriptions [OK]

Common Mistakes:

• Missing dash for list items
• Using singular 'model' instead of 'models'
• Incorrect indentation breaking YAML format

3. Given this YAML snippet in a dbt model file:

models:
  - name: customers
    description: 'Customer details including name and email'
  - name: orders
    description: 'Order records with dates and amounts'

What will dbt documentation show for the 'orders' model?

medium

A. Error loading description

B. Customer details including name and email

C. Order records with dates and amounts

D. No description available

Solution

1. Step 1: Locate the 'orders' model in the YAML snippet

   The 'orders' model is listed with a description: 'Order records with dates and amounts'.

2. Step 2: Understand dbt documentation usage

   dbt uses the description text to show model info in docs.

3. Final Answer:

   Order records with dates and amounts -> Option C

4. Quick Check:

   Model description matches YAML text [OK]

Hint: Match model name to its description in YAML [OK]

Common Mistakes:

• Mixing descriptions between models
• Assuming missing description means error
• Confusing model names

4. You wrote this YAML for a dbt model description but the docs show no description:

models:
  name: products
  description: 'Product catalog details'

What is the likely error?

medium

A. Missing dash (-) before 'name' to define list item

B. Incorrect key 'description' instead of 'desc'

C. YAML does not support descriptions

D. Model name should be uppercase

Solution

1. Step 1: Check YAML list syntax for models

   dbt expects 'models:' followed by a list indicated by '-'. Missing dash means no list item.

2. Step 2: Identify the missing dash before 'name'

   Without '-', YAML treats 'name' as a key under 'models', not a list item, so description is ignored.

3. Final Answer:

   Missing dash (-) before 'name' to define list item -> Option A

4. Quick Check:

   Dash defines list items in YAML [OK]

Hint: Always use dash for list items in YAML [OK]

Common Mistakes:

• Using wrong key names
• Thinking YAML disallows descriptions
• Ignoring YAML indentation rules

5. You want to improve data discoverability by adding descriptions to columns in a dbt model. Which YAML snippet correctly documents the 'customer_id' column with a description?

hard

A. models:
- name: customers
columns:
- name: customer_id
desc: 'Unique ID for each customer'

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

C. models:
- name: customers
columns:
- customer_id: 'Unique ID for each customer'

D. models:
- name: customers
columns:
- name: customer_id
description: 'Unique ID for each customer'

Solution

1. Step 1: Recall correct YAML structure for column documentation in dbt

   Columns are listed as items with '- name:' and 'description:' keys.

2. Step 2: Identify the option matching this structure

   models: - name: customers columns: - name: customer_id description: 'Unique ID for each customer' correctly uses '- name: customer_id' and 'description' key.

3. Final Answer:

   models:\n - name: customers\n columns:\n - name: customer_id\n description: 'Unique ID for each customer' -> Option D

4. Quick Check:

   Correct column description syntax [OK]

Hint: Use '- name:' and 'description:' for columns in YAML [OK]

Common Mistakes:

• Using key-value pairs without dash for columns
• Using 'desc' instead of 'description'
• Incorrect indentation breaking YAML