Author: Steve Zagoudis

Is clean data the same as trusted data?

This article, Steve’s contribution to TDAN, explores why data profiling alone cannot provide enterprise assurance. While profiling identifies anomalies within individual datasets, reconciliation verifies that critical information remains complete, accurate, and consistent across systems and reporting layers.

For risk managers, auditors, and executives, that distinction matters: profiling improves data hygiene; reconciliation provides the evidence needed to trust the data.

Is your Data Governance program delivering measurable business value—or just more buzzwords and technology?

This article, Steve’s contribution to TDAN, challenges organizations to move beyond governance “bling” and view Data Governance as a process control system. By combining Systems Thinking, continuous data quality feedback loops, and governance awareness, organizations can turn metadata and controls into measurable outcomes—reducing data risk, improving efficiency, and demonstrating real ROI.

What if Data Governance worked like a thermostat—continuously detecting and correcting problems before they spread?

This article, Steve’s contribution to TDAN, explores a Systems Thinking approach to Data Governance, replacing reactive fixes with continuous data quality feedback loops. By combining governance metadata, automated controls, and upstream validation, organizations can address problems at their source—reducing manual work, preventing recurring issues, and creating continuous trust in enterprise data.