Data Gathering is an automated system designed to collect, validate, and organize information from multiple sources across an organization in a systematic and efficient manner. The system implements intelligent data extraction techniques to pull information from various formats including documents, databases, emails, and web sources, while maintaining data integrity and proper version control. It includes validation rules to ensure data quality and completeness, automatically flagging discrepancies or missing information for review. The system also maintains detailed documentation of data sources and collection methods for audit purposes.

This system dramatically reduces the time and effort required to collect and organize data from diverse sources, enabling organizations to make faster, data-driven decisions. It significantly improves data quality by implementing consistent validation rules and reducing manual data entry errors. The automated documentation and audit trail capabilities make it easier to track data lineage and ensure compliance with data governance policies. The system's ability to handle multiple data formats and sources makes it valuable for organizations dealing with complex data environments.

The estimate assumes that data sources are accessible and have well-defined APIs or extraction methods. It presumes that data validation rules and quality requirements are already defined and documented. The estimate also assumes that the builder has experience with data integration and ETL processes, as well as familiarity with common data formats and protocols.