Case Study
How UST helped a global analytics company modernize its data infrastructure and save an estimated $10M
OUR CLIENT
This global data and analytics company empowers businesses and consumers to make informed financial decisions through advanced data management, credit insights, and fraud prevention solutions. With operations in dozens of countries worldwide, the company generates billions in annual revenue.
THE CHALLENGE
Rescuing another vendor’s failed data infrastructure modernization project
The company needed to modernize its legacy mainframe data infrastructure to ensure seamless global scalability. It also wanted to eliminate an expensive, third-party on-premises extract, transform, and load (ETL) solution by adopting its in-house cloud-based tool. Attempts by the originally selected vendor failed, leading to delays in project timelines and putting the client in a risky situation. If the company had not completed the migration before the third-party contract renewal deadline, it would have been forced to renew a 3-year multimillion-dollar contract. The company required a trusted partner capable of rescuing the project and delivering the cloud-based ETL transformation, and UST was able to step in.
THE TRANSFORMATION
Delivering a modern, centralized data ingestion platform
UST successfully completed the complex data modernization solution to meet the company’s very tight deadline. Working closely with the company’s technology and business teams to ensure transparency and accountability, UST:
- Implemented a modern, cloud-based data infrastructure solution—eliminating the outdated mainframe technology
- Integrated the company’s in-house ETL solution—replacing the expensive third-party solution
- Established a centralized data ingestion solution—setting the stage for global expansion
- Automated data pipeline build processes—by developing a reusable directed acyclic graph (DAG) framework that uses modular components and enables data scientists to define, reuse, and share pipelines
- Improved performance and scalability—by converting legacy Python scripts to PySpark
THE IMPACT
Projected savings of $10 million and a scalable foundation for global growth
The successful mainframe-to-cloud migration project delivered these quantitative and strategic outcomes for the data analytics company:
- $10 million in projected cost savings—by eliminating the expensive third-party ETL tool and adopting the in-house solution
- Streamlined and modernized data infrastructure—establishing a foundation for scalable data ingestion and enabling the company’s global expansion goals
- Strategic control over the ETL tool—to enhance and extend the solution rather than relying on a third-party vendor
- Better data quality—thanks to the in-house ETL tool’s data matching and deduplication features
Learn more about how UST can help your company with its data modernization needs.
RESOURCES
https://www.ust.com/en/our-approach
https://www.ust.com/en/insights/enabling-data-driven-decision-making