– Custom ETL Solution Client Story –

To provide Voya Financial with an infrastructure to ease growing pains and allow for efficient scalability, Tallan developed an ETL solution that drove more than 80% reduction in customer statements processing time and a 70% reduction in report generation time.


Voya Financial had been experiencing growing pains due to several acquisitions and new business opportunities. Voya needed a system that could handle the new stress as well as further expansion, and they wanted a system architecture that was easy to maintain and also support new investment options for their customers via their Fund Operations System.


Voya Financial Client Story Solution

A Simplified Infrastructure

Tallan designed and implemented an ETL solution conforming to the Voya Financial Enterprise Information Platform standards for data warehousing. This solution allowed Voya to expedite report generation, reduce processing time and enforce data quality. With the data moving from the Sybase source database into downstream UDB databases, Informatica was used to execute the ETL processes.

During ETL development, numerous data quality and audit checks were put in place to ensure the source data conformed to business rules and to ensure the accuracy of data between the source and target. Through these efforts, the existing infrastructure was simplified to reduce the struggle of continued maintenance.

A Custom Workflow

In parallel to the data effort, the Fund Operations application architecture was completely redesigned and greatly simplified to a set of common, reusable, and extendable components, which were organized into an intuitive package structure in the business layer. A custom workflow and sign-off audit process were developed around all system applications.

Performance Improvements

Since implementation, there has been:

  • 70% overall improvement in report generation time
  • Over 80% reduction in customer statements processing time
  • Over 100 data quality scripts written to enforce continued source data quality


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