Embrace Complexity for Clear Insights

A robust ETL process requires balancing clarity and complexity. Initially aimed at data clean-up by removing duplicates and errors, this approach must evolve to support diverse analytical needs across teams. Future requirements, like fraud detection, emphasize the necessity for an adaptable architecture that allows leveraging both processed and raw data for comprehensive analysis without sacrificing integrity or functionality.