Supporting Data Quality Processes with Automated Data Lineage
Data quality is an age-old problem for medium and large enterprises. With enormous swaths of data flowing between numerous complex systems, it is easy for quality issues to go unnoticed. On top of that, the way businesses transform, interpret, select, and move data can introduce new quality issues to datasets. Despite this, many organisations continue to rely on inefficient and error-prone manual tasks to support data quality processes.
Report Snap Shot
This report covers:
- The business applications of high-quality data
- Roadblocks to high data quality