Airlines operate in a highly competitive environment where customer experience, personalization, and operational efficiency are driven by data. However, legacy on-premises data platforms, often built across reservations, ticketing, and loyalty systems, are unable to deliver the speed, scale, and integration required for real-time customer intelligence.
To unlock actionable insights and enable data-driven engagement, airlines are modernizing their data estates with cloud-native platforms that consolidate historical data, support near-real-time analytics, and empower business teams with self-service insights.
The Challenge
The airline’s customer and operational data were fragmented across multiple legacy platforms supporting reservations, ticketing, loyalty, and engagement systems. Large volumes of historical data and complex ETL processes slowed modernization and limited timely access to insights.
Disconnected pipelines across vendors prevented a unified view of the customer, while long ETL execution cycles delayed analytics and decision-making. Limited automation and validation increased the risk of data inconsistencies, and heavy reliance on manual processes restricted self-service analytics for business teams.
Our Approach
Coforge implemented a cloud-based data platform to modernize legacy systems and enable real-time customer intelligence across the airline’s data ecosystem.
Cloud Data Platform Modernization
Migrated legacy on-premises workloads to an AWS-based analytics platform using Amazon Redshift, consolidating large volumes of historical and operational data into a scalable, centralized environment.
Automated Ingestion & Real-Time Processing
Enabled automated ingestion and processing pipelines using AWS Glue, Kinesis, and Spark, significantly reducing ETL execution times and supporting near real-time data availability.
High-Volume Data Transformation
Migrated and transformed 14TB of customer data, modernizing 300+ ETL processes and processing 7B+ historical records efficiently within the cloud environment.
Data Quality, Modeling & Self-Service Analytics
Introduced automated data validation and monitoring to enhance reliability. Implemented an industry-aligned travel data model to standardize customer, booking, and operational datasets, and enabled self-service analytics using Tableau and Alteryx.

Impact to Date
14TB Migrated
7B+ Records Processed
3M+ Records Daily
Key Outcomes
- Unified Analytics Ecosystem Consolidated fragmented Teradata and legacy workloads into a centralized AWS Redshift‑based analytics platform.
- Accelerated Customer Intelligence Enabled near real‑time access to customer and operational insights for marketing and engagement teams.
- Improved Operational Efficiency Reduced manual intervention and downtime through automation, orchestration, and monitoring.
- Future‑Ready Data Foundation Positioned the airline to accelerate predictive analytics, intelligent automation, and next‑generation customer experience initiatives.
By modernizing its legacy data platforms into a scalable, cloud-native analytics solution, Coforge enabled the airline to unlock real-time customer intelligence, improve operational efficiency, and build a future-ready foundation for personalized, data-driven engagement.
