Discover how eligarf transformed the operations of a leading Travel Giant by addressing the complexities of integrating diverse data sources for pricing travel packages. This case study outlines some of the challenges faced, the innovative AWS solutions implemented, and the significant operational efficiencies achieved. 


Customer Challenges:

Our customer, a travel industry giant, was investigating ways to harmonise data from various sources, such as APIs and tools like AWS and Snowflake, complicating data ingestion for base price calculation


eligarf's Solution:

eligarf implemented a unified ingestion mechanism using Confluent Kafka to integrate data from AWS and Snowflake. MongoDB stored structured raw data, while Snowflake was the Cloud Data Warehouse. An event-driven, containerised serverless solution was implemented using AWS services like AWS Fargate, Step Function, Lambda, RDS, OpenSearch, Elastic Cache, Cognito, SNS, SQS, and S3 was deployed to handle data efficiently.

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Customer Benefits:

The solution enabled efficient data handling and base price computation, significantly enhancing operational efficiency. The scalable and cost-effective system supported substantial data volumes, ensuring smooth operations across departments.  

For a detailed understanding of this project, contact us at [email protected] and discover how eligarf can transform your operations with cutting-edge technology and innovation.