Transport & Logistics — Data Normalization and Quality Assurance Pipeline

Overview

The purpose of this DAG is to ensure the integrity and quality of transport and logistics data through systematic normalization and validation processes. The pipeline ingests data from various sources, including ERP transaction logs, GPS tracking data, and customer feedback forms. Upon ingestion, the data undergoes a series of processing steps designed to apply normalization rules and quality checks. These steps include anomaly detection, duplicate identification, and data consistency verificati

The purpose of this DAG is to ensure the integrity and quality of transport and logistics data through systematic normalization and validation processes. The pipeline ingests data from various sources, including ERP transaction logs, GPS tracking data, and customer feedback forms. Upon ingestion, the data undergoes a series of processing steps designed to apply normalization rules and quality checks. These steps include anomaly detection, duplicate identification, and data consistency verification. Each processed dataset is logged to maintain traceability and facilitate audits. The outputs of this pipeline are directed towards a data governance system, which enables ongoing monitoring and compliance with quality standards. Key performance indicators (KPIs) such as error rates and data processing times are tracked to assess the effectiveness of the normalization process. By ensuring high-quality data, this DAG significantly enhances customer personalization initiatives, leading to improved service delivery and customer satisfaction in the transport and logistics industry.

Part of the Customer Personalization solution for the Transport & Logistics industry.

Use cases

• Improved customer experience through personalized services
• Reduced operational risks from inaccurate data
• Enhanced decision-making with reliable data insights
• Streamlined compliance with industry regulations
• Increased efficiency in data handling processes