Why Building a DAG of models in dbt? - Purpose & Use Cases

The Big Idea

What if your data models could update themselves in the perfect order, every time, without you lifting a finger?

The Scenario

Imagine you have many data tables and reports to create, each depending on others. You try to update them one by one, guessing the order. Sometimes you update a table before its source data is ready, causing errors or wrong results.

The Problem

Doing this by hand is slow and confusing. You waste time figuring out which table to update first. Mistakes happen often, and fixing them means redoing work. It's like trying to build a complex puzzle without knowing the right order of pieces.

The Solution

Building a Directed Acyclic Graph (DAG) of models lets you map out all dependencies clearly. The system knows the correct order to run each model automatically. This saves time, avoids errors, and keeps your data pipeline smooth and reliable.

Before vs After

✗ Before

run model_a
delayed run model_b
run model_c before model_b

✓ After

dbt run --models model_c+

What It Enables

It enables automatic, error-free execution of complex data workflows, so you focus on insights, not fixing broken pipelines.

Real Life Example

A marketing team needs daily reports combining customer data, sales, and web traffic. With a DAG, all these models update in the right order every morning without manual checks.

Key Takeaways

Manual updates cause errors and waste time.

DAGs show clear dependencies and run order.

Automated runs make data pipelines reliable and fast.

Practice

1.

What does a DAG represent in dbt?

easy

A. The configuration settings for dbt profiles

B. The syntax rules for writing SQL queries

C. The order in which models depend on each other

D. The list of all tables in the database

Solution

1. Step 1: Understand what DAG means in dbt context

   A DAG (Directed Acyclic Graph) shows how models are connected by dependencies.

2. Step 2: Identify the role of DAG in dbt

   dbt uses the DAG to know which models to run first based on dependencies.

3. Final Answer:

   The order in which models depend on each other -> Option C

4. Quick Check:

   DAG = model dependency order [OK]

Hint: DAG shows model dependencies and run order [OK]

Common Mistakes:

• Confusing DAG with SQL syntax
• Thinking DAG lists all tables
• Mixing DAG with dbt config files

2.

Which of the following is the correct way to reference another model in a dbt SQL file?

SELECT * FROM ___

easy

A. ref(model_name)

B. ref('model_name')

C. 'ref(model_name)'

D. ref:"model_name"

Solution

1. Step 1: Recall the syntax for referencing models in dbt

   dbt uses the function ref() with the model name as a string inside parentheses.

2. Step 2: Check each option for correct syntax

   ref('model_name') uses ref('model_name') which is correct; others have syntax errors or wrong quotes.

3. Final Answer:

   ref('model_name') -> Option B

4. Quick Check:

   Use ref('model_name') with quotes [OK]

Hint: Use ref('model_name') with quotes and parentheses [OK]

Common Mistakes:

• Omitting quotes around model name
• Using wrong quote types
• Using colons or other symbols

3.

Given these two models, what is the order dbt will run them?

-- model_a.sql
SELECT * FROM source_table

-- model_b.sql
SELECT * FROM {{ ref('model_a') }}

medium

A. model_a runs first, then model_b

B. model_b runs first, then model_a

C. Both run simultaneously

D. dbt will error due to circular dependency

Solution

1. Step 1: Identify dependencies from ref()

   model_b references model_a using ref(), so model_b depends on model_a.

2. Step 2: Determine run order based on dependencies

   dbt runs model_a first, then model_b to ensure data is ready.

3. Final Answer:

   model_a runs first, then model_b -> Option A

4. Quick Check:

   Dependency order = model_a before model_b [OK]

Hint: Models run in dependency order: referenced first [OK]

Common Mistakes:

• Assuming ref() means reverse dependency
• Thinking models run simultaneously
• Confusing circular dependency errors

4.

What is wrong with this dbt model code snippet?

SELECT * FROM {{ ref(model_a) }}

medium

A. Model name should be uppercase

B. ref() cannot be used inside SELECT

C. Missing FROM keyword

D. Missing quotes around model name in ref()

Solution

1. Step 1: Check syntax of ref() usage

   ref() requires the model name as a string with quotes inside the parentheses.

2. Step 2: Identify the error in the code snippet

   model_a is not quoted, causing a syntax error in dbt compilation.

3. Final Answer:

   Missing quotes around model name in ref() -> Option D

4. Quick Check:

   ref('model_name') needs quotes [OK]

Hint: Always put model names in quotes inside ref() [OK]

Common Mistakes:

• Forgetting quotes around model names
• Thinking ref() can't be in SELECT
• Assuming case sensitivity causes error

5.

You have three models: model_x, model_y, and model_z. model_y references model_x, and model_z references both model_x and model_y. Which of the following is the correct order dbt will run these models?

hard

A. model_x, model_y, model_z

B. model_y, model_x, model_z

C. model_z, model_y, model_x

D. model_x, model_z, model_y

Solution

1. Step 1: Analyze dependencies among models

   model_y depends on model_x; model_z depends on both model_x and model_y.

2. Step 2: Determine run order respecting dependencies

   model_x runs first (no dependencies), then model_y (depends on model_x), then model_z (depends on both).

3. Final Answer:

   model_x, model_y, model_z -> Option A

4. Quick Check:

   Run order respects dependencies [OK]

Hint: Run models so dependencies are built before dependents [OK]

Common Mistakes:

• Running dependent models before their dependencies
• Ignoring multiple dependencies
• Assuming any order works if models reference each other