Overview: This project involved designing and implementing an end-to-end ETL (Extract, Transform, Load) solution to streamline data workflows and enhance operational efficiency for a client. The aim was to improve data accuracy, reduce processing times, and provide reliable insights for decision-making.

Data Extraction: Automated data extraction from multiple sources, including databases, and flat files.

Data Transformation: Applied cleaning, deduplication, and business logic to standardize and enrich data for analysis.

Data Loading: Efficiently loaded processed data into a centralized data warehouse for seamless accessibility.

Error Handling: Built robust mechanisms to detect and handle data inconsistencies during processing.

Scheduling and Automation: Integrated scheduled workflows to ensure timely data updates without manual intervention.

Impact: The ETL solution delivered:

Faster data processing, reducing manual intervention by 80%.

Enhanced data quality, minimizing errors and inconsistencies.

Real-time insights availability, supporting agile decision-making.

Scalable architecture, enabling future growth and system expansion.