Implement Data Quality Checks in an Airflow Pipeline with Soda: Step-by-Step Tutorial

Run Soda Data Quality Checks in an Airflow Pipeline

This tutorial guides you through the steps to quickly set up and run Soda data quality checks within an Airflow pipeline. Learn how to install Soda packages, configure Soda Cloud, and execute data quality checks.

Step 1: Set Up Soda Cloud

Log in to yur oda Club account. If you don't have an account, visit soda.io and start a free trial.

ASSIST: SET UP SODA

Step 2: Design the Airflow Pipeline

The Airflow DAG will include operators to process data, with Soda Python operators integrated after each stage to run data quality checks.

Example pipeline structure:

1. Ingest data: process raw data.
2. Transform data: apply transformations (e.g., with dbt).
3. Publish data: load transformed data into the production warehouse.

At each step, a Soda scan will test the data quality before proceeding to the next stage.

Step 3: Install the Soda Python Library

Ensure the Soda Python Library is installed in the virtual environment running the Airflow DAG. This package enables you to perform scans and interact with Soda Cloud.

ASSIST: INSTALL SODA LIBRARY

Step 4: Configure Soda YAML Files

Set up the required configuration files:

• Configuration YAML: define the data source and Soda Cloud connection details.
• Checks YAML: define specific data quality checks for your dataset.

Step 5: Define the Soda Scan Function

Write a Python function to execute the Soda scan:

1. Import the Soda Scan object.
2. Point the scan to the Configuration YAML and Checks YAML.
3. Define the dataset name and attributes (metadata).
4. Execute the scan and return results.

Step 6: Integrate Soda Scans in the DAG

Use the Soda scan function within Python operators in your DAG.

Step 7: Analyze Results in Soda Cloud

Once the DAG runs, all Soda scan results are pushed to Soda Cloud:

• UI features:
  • View dataset health scores and check statuses.
  • Analyze failed rows and historical trends.
• Configure Soda Cloud to only store links to failed rows if sensitive data cannot be exposed.

ASSIST: REVIEW RESULTS

Step 8: Set Up Alerts

Soda integrates with communication tools like Slack, JIRA, and Microsoft Teams so you can configure alert notifications when data quality checks warn or fail. Set up the integration in your avatar > Organization Settings > Integrations. For example:

• Use attributes like Pipeline Stage to customize alerts by stage.
• When checks fail, Soda sends a notification to a specific Slack channel and includes a link to Soda Cloud for investigation.
• Send alerts for ingestion checks to one group and transformation checks to another.

ASSIST: SET ALERT NOTIFICATIONS

Step 9: Advanced Reporting

Extract scan results and metadata using the Soda Cloud API to build customized reports. For example:

• Classify checks by pipeline stage or data team ownership.
• Generate dashboards to monitor the health of your data pipelines.

ASSIST: SODA CLOUD REPORTING API

Step 10: Circuit Breakers for Data Pipelines

Leverage Soda's assert check fail feature to stop the pipeline if critical checks fail, preventing bad data from reaching production.