Enhancing Retail Data Quality with Apache Airflow on GCP

Executive Summary

In the retail industry, ensuring the quality and integrity of data is crucial for maintaining customer satisfaction and making informed business decisions. A leading retail giant in the US faced challenges with managing data quality within their loyalty program stored in a Google Cloud Platform (GCP) data lake. Factspan introduced an automated solution using Apache Airflow to streamline data quality scans. This integration with Google Cloud Dataplex enhanced data accuracy, reduced manual intervention, and improved operational efficiency, enabling swift and informed decision-making.

Factspan’s solution fundamentally changed how the client ensures data quality, automating processes and democratizing insights. This integrated system ensured that they maintained their competitive edge by providing accurate and timely data for decision-making.

About the Client

A major retail conglomerate in the US that offers a diverse range of products, including fashion and home goods. They operate an extensive loyalty program to enhance customer engagement. Their commitment to delivering exceptional customer experiences drives their focus on maintaining high-quality data and leveraging advanced technology solutions.

Business Challenge

The organization struggled with ensuring the quality of data within their loyalty program. Inconsistent and erroneous data led to poor decision-making and negatively impacted customer experiences which in turn impacted their revenue in the long run. The challenge was to automate data quality scans in their GCP data lake to maintain ongoing data integrity without manual intervention.

Our Solution

Factspan developed a workflow using Apache Airflow to automate the creation and execution of data quality scans in Google Cloud Dataplex. This solution integrated seamlessly with the client’s existing infrastructure and consisted of the following components:

The team created a new Apache Airflow DAG with tailored parameters to ensure correct task workflows and dependencies. Scheduled to start on a specific date without catching up on missed runs, The YAML file is stored in Google Cloud Storage and is used by Dataplex to determine the data quality specifications for performing data quality scans. Managed through Google Cloud Composer, this setup streamlined our Airflow environment with GCP integration.

For data quality, Google Cloud Dataplex was used to create and execute scans via BashOperator and PythonOperator within the DAG. Integrated with BigQuery, these scans ensured high standards for our loyalty program data. Results and metrics were stored in the summary table in BigQuery, providing a centralized location for analysis and review.

Implementing this solution has significantly improved the client’s ability to maintain high data quality standards in their loyalty program. By automating data quality scans using Apache Airflow and Google Cloud Dataplex, the client has streamlined their data management processes, leading to more accurate and reliable data for business decision-making. The effectiveness of combining Apache Airflow’s orchestration capabilities with Google Cloud’s data management tools achieved robust and scalable data quality checks. Explore our data quality solutions to enhance operational efficiency in retail.

Business Impact

• Automation: Reduced manual effort by 50%
• Scalability: Increased data quality scans by 30%
• Data Quality: Improved data accuracy by 20%
• Integration: Enhanced integration efficiency by 40%