Online Travel Agency Case Study

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3x

expected growth in data platform over 2 years

50%

reduced TCO

1,500

analytics user

Region

Americas

Industry

Other

Solution

Enterprise

Employees

1000+

“Our old engine didn’t support Iceberg. We needed Starburst to move forward with the next generation data lakehouse format. We also wanted to avoid vendor lock-in. That was a big factor in selecting Starburst.”

Anonymous, Analytics Tooling Manager

3x

expected growth in data platform over 2 years

50%

reduced TCO

1,500

analytics user

About

One of the world’s leading full-service online travel brands recognized the critical role data-driven decisions play in the fast-paced world of online travel and hospitality. Its mission is to harness the potential of data to elevate customer experiences and streamline internal processes for its vast analyst and business community. However, the travel agency faced challenges in unifying their diverse data lakes and needed a solution that would provide compatibility, performance, and the ability to scale seamlessly.

Challenge

The customer’s multi-year data lakehouse unification journey aimed to shift focus from brand-centric to customer-centric data. With disparate data lakes across different brands and over 70 petabytes of data, integrating and centralizing data became a significant challenge. The reliance on an outdated PrestoDB query engine led to performance issues and limited end-of-life support, resulting in potential outages.

Additionally, having Looker as their only source for business insights hindered the Customer Care department’s ability to provide comprehensive and personalized support.

Solution

Starburst’s support for open-source tools like Trino and Apache Iceberg aligned perfectly with the online travel agency’s goal to avoid vendor lock-in and retain independence. As one of the early adopters of the open-source Trino query engine, the company was familiar with its capabilities and recognized it as a powerful tool for data analytics. When it came to selecting a solution for scaling their data analytics environment, it was a natural fit to adopt Starburst Enterprise.

Additionally, Starburst met the following requirements:

Concurrency. The ability to run multiple workloads simultaneously to feed BI dashboards.
Fine grained access control. Column-level access controls.
Stability / availability. Easy to support.
Performance. Meets SLAs for query speeds (<5 seconds) with high concurrency.
Integration with existing BI tools. Compatible with Looker, Tableau, Jupyter, and R Studio.
Scalability. No idle resources; can be deployed on EC2 instances via Terraform.
Customizable. Connect to the agency’s existing environment, which includes custom Ranger solutions and custom meta stores).

The transition to Starburst allows the online travel agency to leverage modern data lakehouse constructs, particularly Apache Iceberg and Amazon S3, for enhanced analytics. Iceberg provides transactional consistency, schema evolution, and efficient data partitioning, which are essential for managing large datasets and ensuring data integrity. The modern architecture opened up a wealth of data for the Customer Care department, providing them with access to a comprehensive view of their data landscape, and enabling them to deliver more personalized and effective support to travelers.

Results

The implementation of Starburst Enterprise and Apache Iceberg proved successful for the online travel agency. They experienced a significant improvement in query performance, allowing for faster decision-making and improved self-service analytics. Immediate access to data due to the reduction of ETL, coupled with the ability to scale clusters for enhanced query performance has improved the analytics workflow of over 1,500 users. The company has also achieved a 50% reduction in Total Cost of Ownership (TCO), making data storage in the data lakehouse significantly more cost-effective over the traditional cloud data warehouse.

As the travel agency anticipates a 3X growth in their data platform over the next 2 years, Starburst’s scalability and lower TCO will continue to expand savings over time. The company is now poised to achieve commoditized analytics, leading to greater cost savings and increased operational efficiency. Ultimately, the collaboration has unlocked the true potential of their data lakehouse, setting a path towards long-term success.

“Starburst Enterprise has not only transformed our analytics capabilities but has also enabled us to achieve insights at an unprecedented speed, fueling our ability to drive business strategies forward,” shares the Analytics Tooling Manager.