Case Study
Global fintech uses automated data migration workflow from UST to cleanse, encrypt, migrate eight GBs of data a month
OUR CLIENT
Founded more than a century ago, this global financial services company provides consumer credit data to millions of business around the world as well as credit monitoring and fraud prevention services. The company employs more than 10,000 people and generates approximately $5 billion in annual revenue.
THE CHALLENGE
Legacy system-to-data fabric migration challenges—cleansing, ingesting, ensuring high-quality information
After modernizing its legacy data storage infrastructure with a data fabric, the company struggled to cleanse and migrate large volumes of data to the new system. The outdated data formats created quality and consistency challenges and didn’t allow seamless migration to the new data fabric. The fintech company needed a seasoned IT partner with deep data engineering expertise to lead the project.
THE TRANSFORMATION
Automated data engineering workflow ensures seamless migration process
UST created an automated data encryption, cleansing, ingestion, and refresh process using Google Cloud Platform (GCP) technologies, including Dataflow, Cloud Storage, Bigtable, Cloud Composer, and BigQuery. The data fabric solution creates a mirror copy of the company’s database. Data sets are encrypted, using the pretty good privacy (PGP) format, cleansed, and ingested into the modern production data storage solution using the data fabric admin portal. The original database continues to ingest data from data providers. New data sets follow the data fabric encryption, cleansing, and ingestion workflow every month to ensure the new, modern data storage solution is always up to date and ready for end-user customer analysis.
THE IMPACT
Holistic improvements in data quality, productivity, efficiencies, and customer experiences
Now, the company has a fully automated, secure process to migrate a monthly volume of eight GBs of data from its legacy data storage system to a new data fabric storage solution. The seamless workflow has contributed to these results:
- Improved data quality and consistency—by embedding secure, automated cleansing processes in the data migration workflow
- Better business insights and customer experiences—from readily-available, clean, up-to-date data, enabling end-user customers to make more informed credit and fraud prevention decisions
- Increased operational efficiencies—from end-to-end automated data migration workflows that save time and reduce errors
- Enhanced productivity—since the IT team and data analysts no longer have to deal with manual data migration processes, allowing them to focus on value-added tasks, such as analysis and interpretation
Find out how UST Cloud Services can optimize your data management and migration processes.
RESOURCES
https://www.ust.com/en/what-we-do/digital-transformation/data-analytics