Advanced Data Lake Implementation for Global Travel Data Management

The client faces difficulties integrating diverse legacy systems, managing rapidly escalating data volumes from multiple sources, and streamlining data processes to deliver tailored travel solutions. The growth through acquisitions exacerbates data silos and hampers real-time insights.

A large-scale online travel company operating in multiple countries, offering multi-leg flight bookings with diverse airline partnerships, seeking to optimize its data infrastructure.

• Aggregate and centralize vast volumes of structured, semi-structured, and unstructured travel data from multiple sources into a unified data lake.
• Implement real-time Change Data Capture (CDC) mechanisms to enable live data updates and online processing.
• Automate data cleaning, deduplication, and relationship identification to improve data quality and facilitate advanced analytics.
• Develop dashboards and reporting tools to support data-driven decision-making and personalized customer offerings.
• Design scalable and flexible system architecture that supports future technological integrations and international expansion.
• Reduce operational costs associated with data processing and storage through centralized automation.

• Data aggregation from multiple heterogeneous sources into a centralized repository.
• Support for structured, semi-structured, and unstructured data formats.
• Real-time Change Data Capture (CDC) to enable live data synchronization.
• Data cleaning, error removal, and deduplication modules.
• Relationship analysis and dependency mapping within travel data.
• Generation of business intelligence reports and dashboards.
• Scalable architecture facilitating future AI/ML integration.
• Automated data workflows via ETL processes.

• Multiple airline and booking system APIs for comprehensive data ingestion.
• Existing legacy systems for seamless data transfer.
• Business intelligence tools for reporting and visualization.
• Data storage solutions for scalable data persistence.

• Support for data volumes exceeding several terabytes with high-throughput ingestion.
• Real-time data processing latency below 1 minute for live updates.
• High system availability and fault tolerance.
• Data security and compliance with industry standards (e.g., GDPR).
• Scalability to accommodate doubling of data volume growth within 2 years.

Implementing a centralized, real-time travel data lake is expected to enhance decision-making speed and accuracy, reduce operational costs by automating data workflows, and improve market competitiveness through better customer personalization. The scalable architecture will support future analytics expansion with AI and ML, enabling the client to identify new growth opportunities across international markets.