Data platform transformation reduces ETL costs by 90%

A global leader in the pharmaceutical industry resolved significant challenges in data processing and synchronization. The project focused on costly inefficiencies across multiple siloed infrastructures that utilized early-stage, untested frameworks.

‍

By implementing a platform-agnostic solution leveraging AWS, Redshift, and DBT, the team achieved a 90% reduction in ETL processing costs and enabled real-time reporting. Financial report accuracy improved by 30%, and end-of-month data processing time was drastically cut from 8 days to less than one day.

‍

The approach included full automation, rapid solution rebuilding, and the adoption of best software engineering and DevOps practices, which facilitated a coordinated development, testing, and production process throughout the software lifecycle.

‍