- Streamlined Document Processing
By moving PDF ingestion and title extraction to Databricks using Python, the team eliminated legacy complexity and reduced processing times, enabling faster delivery of usable data.
- Improved Scalability and Maintainability
Refactoring critical logic into Databricks allowed for better visibility and monitoring, making the workflows easier to update and scale across growing data loads.
The unified data pipelines and standardized schemas reduced the time between data ingestion and usable insights, helping teams respond more quickly to market opportunities.
Post-migration, the consolidated data structures and Snowflake integrations ensured stronger auditability and schema compliance.
