Radhamani Textiles
Outcome
Streamlined data processes with improved processing efficiency, reduced monthly subscription and operational costs, better scalability, and enhanced data accuracy providing reliable foundation for future business intelligence initiatives.
Challenge
- Fashion retail business faced high costs
- limited scalability from dependence on third-party data pipeline tools for transferring retail data from Google Cloud Storage to BigQuery
- Required more economical solution for growing business intelligence needs
Implementation
- econz re-engineered data pipeline workflows
- switching from Dataprep to native GCP services including Data Fusion
- optimized data processing for retail operations
