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 organizations continue to rely on inefficient and error-prone manual tasks to support data quality processes. Fortunately, there is a better way to ensure data quality: automated data lineage.

Automated data lineage maps out organizations’ complete data flows from start to finish, eliminating the negative consequences of using poor-quality data to drive business decisions. Consult this guide, courtesy of MANTA, to learn more:


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