Retail — E-Commerce Data Quality Monitoring Pipeline

Overview

The purpose of this DAG is to ensure the integrity and reliability of data used within the e-commerce search engine by implementing a comprehensive data quality monitoring system. It ingests data from multiple sources, including customer transaction logs, product inventory databases, and user activity records. The ingestion pipeline is designed to efficiently collect and preprocess this data for subsequent validation. The processing steps involve conducting a series of quality control tests, suc

The purpose of this DAG is to ensure the integrity and reliability of data used within the e-commerce search engine by implementing a comprehensive data quality monitoring system. It ingests data from multiple sources, including customer transaction logs, product inventory databases, and user activity records. The ingestion pipeline is designed to efficiently collect and preprocess this data for subsequent validation. The processing steps involve conducting a series of quality control tests, such as completeness checks, consistency validations, and accuracy assessments. When any issues are detected, alerts are generated to notify relevant stakeholders, enabling prompt resolution. The outputs of this DAG are integrated into a data quality dashboard that visualizes key performance indicators (KPIs) such as error rates, validation success rates, and data completeness metrics. Continuous monitoring of these KPIs allows for ongoing assessment of the data quality controls' effectiveness. The business value lies in enhancing the reliability of search results, thereby improving customer satisfaction and driving sales growth in the retail sector.

Part of the Literature Review solution for the Retail industry.

Use cases

• Increased trust in data-driven decision-making
• Enhanced customer satisfaction through reliable search results
• Reduced operational risks from poor data quality
• Improved efficiency in data management processes
• Higher sales conversion rates due to accurate product information