DBT : Building Robust Tests in DBT – Guardians of Data Quality


Data quality is the backbone of any data-driven decision-making process, and DBT (Data Build Tool) plays a crucial role in ensuring that quality. In this article, we’ll explore how to approach building robust tests in DBT to safeguard data quality across various data models. We’ll dive into custom test creation, anomaly detection, consistency checking, and handling null values, complete with examples.

1. Custom Test Creation in DBT

DBT allows you to write custom tests that fit your specific data models and requirements.

Example: Custom Test for Value Range
-- tests/freshers_value_range_test.sql
WITH data AS (
  SELECT my_column
  FROM {{ ref('freshers_audit_table') }}
FROM data
WHERE my_column < 0 OR my_column > 100

This test checks if the values of my_column fall outside the range 0 to 100.

2. Anomaly Detection

Anomalies can point to underlying issues in the data. Anomaly detection helps identify unexpected patterns.

Example: Anomaly Detection Using Standard Deviation
-- tests/anomaly_detection.sql
WITH data_stats AS (
  SELECT AVG(sale_amount) AS avg_amount,
         STDDEV(sale_amount) AS stddev_amount
  FROM {{ ref('freshers_audit_sales') }}
, anomalies AS (
  SELECT sale_amount
  FROM {{ ref('freshers_audit_sales') }}
  JOIN data_stats
  ON ABS(sale_amount - avg_amount) > 3 * stddev_amount
FROM anomalies

This test identifies sales amounts that are three standard deviations away from the average, signaling potential anomalies.

3. Consistency Checking

Consistency checks ensure that data adheres to expected relationships or constraints.

Example: Foreign Key Consistency Test
-- tests/foreign_key_consistency.sql
SELECT customers.customer_id
FROM {{ ref('customers') }} customers
LEFT JOIN {{ ref('freshers_audit_orders') }} orders
ON customers.customer_id = orders.customer_id
WHERE orders.customer_id IS NULL

This test checks if there are any customer IDs in the ‘customers’ table that do not exist in the ‘orders’ table.

4. Handling Null Values

Handling and testing for null values are crucial for maintaining data integrity.

Example: Null Value Test for Mandatory Fields
-- tests/null_value_test.sql
FROM {{ ref('freshers_employees') }}
WHERE first_name IS NULL OR last_name IS NULL

This test ensures that the ‘first_name’ and ‘last_name’ fields in the ’employees’ table are not null.

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