dbt-expectations for data quality - Mini Project: Build & Apply

Data Quality Checks with dbt-expectations

📖 Scenario: You work as a data analyst in a retail company. You want to make sure the sales data you use is clean and reliable before making reports. Using dbt-expectations, you will add simple data quality tests to your sales data model.

🎯 Goal: Build a dbt model for sales data and add dbt-expectations tests to check for missing values and valid ranges. Finally, run the tests and see the results.

📋 What You'll Learn

Create a dbt model file with sample sales data

Configure the model to materialize as a table

Write dbt-expectations tests to check for nulls and valid sales amounts

Run the tests and print the test results

💡 Why This Matters

🌍 Real World

Data analysts and engineers use dbt-expectations to automate data quality checks and catch errors early in data pipelines.

💼 Career

Knowing how to write and run data quality tests with dbt-expectations is a valuable skill for data engineers and analytics engineers.

1

Create a dbt model with sample sales data

Create a dbt model file called sales.sql with a select statement that returns these exact rows: order_id 1, 2, 3; customer_id 101, 102, 103; and sales_amount 100, NULL, 250.

dbt

-- Create a dbt model called sales.sql with the specified rows
-- Your code here

Need a hint?

Use a select * from (values ...) statement with the exact rows and column names.

2

Enable dbt-expectations in the model config

Add a config block at the top of sales.sql to set materialized to table.

dbt

{% raw %}{% config(
  materialized='table'
) %}{% endraw %}

select * from (values
  (1, 101, 100),
  (2, 102, null),
  (3, 103, 250)
) as sales(order_id, customer_id, sales_amount)

-- Add the config block above the select statement
-- Your code here

Need a hint?

Use the {% config() %} Jinja block at the top of the model file.

3

Add dbt-expectations tests for data quality

Create a test file called test_sales.yml with dbt-expectations tests: one to check sales_amount has no nulls using expect_column_values_to_not_be_null, and one to check sales_amount values are between 0 and 1000 using expect_column_values_to_be_between.

dbt

# Create test_sales.yml with dbt-expectations tests
# Your code here

Need a hint?

Use YAML format with models and tests keys. Add the two dbt-expectations tests exactly as shown.

4

Run dbt tests and print the results

Run dbt test --select sales in your terminal and print the summary line that shows how many tests passed and failed.

dbt

# Run 'dbt test --select sales' in terminal
# Print the summary line below
# Your code here

Need a hint?

Run the dbt test command and print the exact summary line showing test results.