Real-Time Data Pipeline Optimization for Enhanced Flight Operations

In the competitive Airlines & Aviation industry, timely and accurate data is crucial for optimizing flight operations. Our mid-sized airline faces challenges with the existing data pipeline's latency and accuracy, impacting operational decisions and customer satisfaction. This project aims to revamp the real-time data pipeline using a suite of advanced technologies including Apache Kafka for event streaming, Spark for in-memory data processing, and Databricks for scalable data analytics. The integration of Airflow will streamline workflow automation, while dbt will ensure robust data transformations. By employing a data mesh architecture, we aim to decentralize and democratize data access across the organization, enabling real-time analytics and insights. The project will also incorporate data observability practices to ensure data quality and reliability. Through this initiative, the airline anticipates a significant improvement in operational efficiency and customer experience, directly impacting revenue and competitiveness in the market.