Why Variables and control flow in dbt? - Purpose & Use Cases

The Big Idea

What if you could change your entire data analysis with just one setting instead of hunting through hundreds of lines of code?

The Scenario

Imagine you have a big data project where you need to run the same analysis but with different settings each time. You try to change values everywhere manually in your SQL files and scripts.

Every time you want to test a new scenario, you have to find and replace numbers or conditions in many places.

The Problem

This manual way is slow and confusing. You might forget to change some values or make mistakes that break your queries.

It's hard to keep track of what settings you used for each run, and fixing errors takes a lot of time.

The Solution

Using variables and control flow in dbt lets you write flexible code that changes behavior based on simple settings.

You define variables once and use them everywhere. Control flow lets you decide which parts of your code run depending on those variables.

This makes your project easier to manage, test, and update.

Before vs After

✗ Before

SELECT * FROM sales WHERE region = 'North';
-- Change 'North' manually for each region

✓ After

SELECT * FROM sales WHERE region = '{{ var("region_name", "North") }}';
{% if var("region_name") == "North" %}
  -- special logic for North
{% endif %}

What It Enables

You can build smart, reusable data models that adapt automatically to different needs without rewriting code.

Real Life Example

A data analyst wants to generate monthly reports for different regions. Instead of copying queries for each region, they use variables to switch regions and control flow to customize filters, saving hours of work.

Key Takeaways

Variables let you store values once and reuse them everywhere.

Control flow helps your code make decisions based on those variables.

Together, they make your data projects flexible, easier to maintain, and less error-prone.

Practice

1. What does the {% set %} statement do in dbt?

easy

A. It deletes a table from the database.

B. It runs a SQL query directly.

C. It defines a new model in dbt.

D. It creates a variable to store a value for reuse.

Solution

1. Step 1: Understand the purpose of {% set %}

   The {% set %} statement in dbt is used to create a variable that holds a value.

2. Step 2: Identify its use in code reuse

   This variable can then be reused multiple times in your dbt project, making code cleaner and easier to maintain.

3. Final Answer:

   It creates a variable to store a value for reuse. -> Option D

4. Quick Check:

   {% set %} creates variables [OK]

Hint: Remember: {% set %} means 'store this value' [OK]

Common Mistakes:

• Thinking {% set %} runs SQL directly
• Confusing it with model creation
• Assuming it deletes data

2. Which of the following is the correct syntax to create a variable named my_var with value 10 in dbt?

easy

A. {% set my_var = 10 %}

B. {% var my_var = 10 %}

C. {{ set my_var = 10 }}

D. {% set 'my_var' = 10 %}

Solution

1. Step 1: Recall dbt variable syntax

   In dbt, variables are created using the Jinja syntax: {% set variable_name = value %}.

2. Step 2: Check each option

   {% set my_var = 10 %} matches the correct syntax exactly. Options B and C use wrong keywords or delimiters. {% set 'my_var' = 10 %} incorrectly quotes the variable name.

3. Final Answer:

   {% set my_var = 10 %} -> Option A

4. Quick Check:

   Correct variable syntax uses {% set %} [OK]

Hint: Use {% set var = value %} without quotes around var [OK]

Common Mistakes:

• Using {{ }} instead of {% %} for setting variables
• Quoting variable names incorrectly
• Using wrong keywords like var

3. Given the following dbt code snippet, what will be the output of {{ greeting }}?

{% set hour = 15 %}
{% if hour < 12 %}
  {% set greeting = 'Good morning' %}
{% elif hour < 18 %}
  {% set greeting = 'Good afternoon' %}
{% else %}
  {% set greeting = 'Good evening' %}
{% endif %}
{{ greeting }}

medium

A. Good morning

B. Good evening

C. Good afternoon

D. No output (error)

Solution

1. Step 1: Evaluate the value of hour

   The variable hour is set to 15.

2. Step 2: Check the if-elif-else conditions

   Since 15 is not less than 12, the first condition fails. It is less than 18, so the second condition is true, setting greeting to 'Good afternoon'.

3. Final Answer:

   Good afternoon -> Option C

4. Quick Check:

   15 < 18 -> 'Good afternoon' [OK]

Hint: Check conditions in order; first true branch runs [OK]

Common Mistakes:

• Assuming hour 15 is morning
• Ignoring elif and jumping to else
• Thinking variable is undefined

4. Identify the error in this dbt snippet:

{% set total = 0 %}
{% for i in range(3) %}
  {% set total = total + i %}
{% endfor %}
{{ total }}

medium

A. The range function is not available in dbt Jinja.

B. Variables cannot be updated inside a loop.

C. The loop syntax is incorrect; missing parentheses.

D. The variable total should be declared with var.

Solution

1. Step 1: Understand Jinja in dbt limitations

   dbt uses Jinja templating, which does not support Python's range() function directly.

2. Step 2: Identify the error cause

   Using range(3) will cause an error because range is undefined in this context.

3. Final Answer:

   The range function is not available in dbt Jinja. -> Option A

4. Quick Check:

   No range() in dbt Jinja [OK]

Hint: Remember: Jinja loops use lists, not Python range() [OK]

Common Mistakes:

• Assuming Python functions work in Jinja
• Trying to update variables inside loops without workarounds
• Using wrong loop syntax

5. You want to create a dbt model that uses a variable env to switch between two schemas: dev_schema if env is 'dev', else prod_schema. Which code snippet correctly implements this control flow?

hard

A. {% set schema = 'dev_schema' if env == 'dev' else 'prod_schema' %}
SELECT * FROM {{ schema }}.my_table

B. {% if env == 'dev' %}
{% set schema = 'dev_schema' %}
{% else %}
{% set schema = 'prod_schema' %}
{% endif %}
SELECT * FROM {{ schema }}.my_table

C. {% set schema = env == 'dev' and 'dev_schema' or 'prod_schema' %}
SELECT * FROM {{ schema }}.my_table

D. {% set schema = 'prod_schema' %}
{% if env == 'dev' %}
{% set schema = 'dev_schema' %}
SELECT * FROM {{ schema }}.my_table

Solution

1. Step 1: Understand conditional variable assignment in dbt

   dbt supports control flow with {% if %} and {% else %} blocks to set variables based on conditions.

2. Step 2: Check each option for correctness

   {% if env == 'dev' %} {% set schema = 'dev_schema' %} {% else %} {% set schema = 'prod_schema' %} {% endif %} SELECT * FROM {{ schema }}.my_table uses proper if-else blocks to set schema correctly before using it in the query. {% set schema = 'dev_schema' if env == 'dev' else 'prod_schema' %} SELECT * FROM {{ schema }}.my_table uses Python-style inline if which is not supported in Jinja. {% set schema = env == 'dev' and 'dev_schema' or 'prod_schema' %} SELECT * FROM {{ schema }}.my_table uses a Python boolean expression which is not valid in Jinja. {% set schema = 'prod_schema' %} {% if env == 'dev' %} {% set schema = 'dev_schema' %} SELECT * FROM {{ schema }}.my_table sets schema first then tries to reset inside if but the query is inside the if block, causing scope issues.

3. Final Answer:

   Option B correctly uses if-else to set schema and then queries it. -> Option B

4. Quick Check:

   Use {% if %}...{% else %}...{% endif %} for control flow [OK]

Hint: Use full if-else blocks to set variables, not inline Python [OK]

Common Mistakes:

• Trying Python inline if syntax in Jinja
• Placing SQL inside if blocks incorrectly
• Not setting variable before using it