Why project structure scales with team size in dbt - See It in Action

Why project structure scales with team size

📖 Scenario: You are part of a growing data team using dbt to manage data transformations. As more team members join, organizing your dbt project well becomes important to keep work clear and efficient.

🎯 Goal: Build a simple dbt project structure that shows how to organize models by team responsibility to help scale work as the team grows.

📋 What You'll Learn

Create a dictionary called models with keys as team names and values as lists of model names

Create a variable called team_to_focus and set it to the team name to analyze

Use a for loop with variables model to get all models for the selected team from models

Print the list of models for the selected team

💡 Why This Matters

🌍 Real World

In real data teams, organizing dbt models by team or function helps avoid confusion and merge conflicts as more people work on the project.

💼 Career

Data engineers and analysts often collaborate on dbt projects. Knowing how to structure projects for team scaling is a valuable skill.

1

Create the dbt project model structure

Create a dictionary called models with these exact entries: 'analytics': ['user_activity', 'sales_summary'], 'engineering': ['raw_events', 'staging_users'], 'marketing': ['campaign_performance', 'lead_scoring']

dbt

# Create the models dictionary with team keys and model lists
# Your code here

Need a hint?

Use curly braces to create a dictionary. Keys are team names as strings, values are lists of model names.

2

Select the team to focus on

Create a variable called team_to_focus and set it to the string 'analytics'

dbt

models = {
    'analytics': ['user_activity', 'sales_summary'],
    'engineering': ['raw_events', 'staging_users'],
    'marketing': ['campaign_performance', 'lead_scoring']
}
# Set the team_to_focus variable to 'analytics'
# Your code here

Need a hint?

Assign the string 'analytics' to the variable team_to_focus.

3

Get models for the selected team

Create a list called selected_models by using a for loop with variable model to iterate over models[team_to_focus] and collect each model

dbt

models = {
    'analytics': ['user_activity', 'sales_summary'],
    'engineering': ['raw_events', 'staging_users'],
    'marketing': ['campaign_performance', 'lead_scoring']
}

team_to_focus = 'analytics'

# Use a for loop to create selected_models list from models[team_to_focus]
# Your code here

Need a hint?

Use a list comprehension with model iterating over models[team_to_focus].

4

Print the selected team's models

Write a print statement to display the selected_models list

dbt

models = {
    'analytics': ['user_activity', 'sales_summary'],
    'engineering': ['raw_events', 'staging_users'],
    'marketing': ['campaign_performance', 'lead_scoring']
}

team_to_focus = 'analytics'

selected_models = [model for model in models[team_to_focus]]

# Print the selected_models list
# Your code here

Need a hint?

Use print(selected_models) to show the list of models.