Problem

A government agency was operating on an aging Precisely Data Quality platform that no longer met its scalability, automation, or governance needs. The tool was costly to maintain, difficult to extend, and lacked modern capabilities required for enterprise‑level data quality monitoring. The agency selected Ataccama as its next‑generation Data Quality platform.

Approach

• Supported the full decommissioning of Precisely, ensuring existing rules, workflows, and monitoring logic were documented and transitioned.
• Identified dependencies, rule logic, and data flows that needed to be replicated or redesigned in Ataccama.
• Ensured a clean cutover by validating that Ataccama could support all required rule types, monitoring frequencies, and reporting needs.

• Collaborated with PrinceIT personnel responsible for implementing Ataccama, providing guidance on rule design, configuration, and best practices.
• Helped define the initial rule library, aligning rule logic to business expectations and regulatory requirements.
• Supported the onboarding of Business Units, ensuring they understood how to interpret results, validate issues, and request new rules.

• Designed and implemented a Data Quality Incident Management process issue classification, severity levels, ownership and routing, escalation paths, and resolution workflows
• Created a Reporting Management process to standardize how DQ results were communicated to stakeholders, including dashboards, summaries, and trend analysis.
• Ensured both processes aligned with the agency’s governance structure and compliance requirements.
• Provided hands‑on support to PrinceIT and Business stakeholders to ensure they could operate Ataccama independently.

• Delivered training on rule creation, monitoring, issue triage, and reporting.
• Helped establish a repeatable model for expanding the DQ program over time.

Outcome

• Successfully retired the Precisely Data Quality platform with no disruption to business operations.
• Enabled the agency to fully adopt Ataccama as its enterprise Data Quality solution.
• Established modern, scalable DQ processes, including automated monitoring, issue management, and reporting.
• Strengthened collaboration between IT, governance teams, and Business Units through clear workflows and ownership models.
• Increased data trust and transparency by providing consistent, actionable Data Quality insights.
• Positioned the agency for long‑term maturity, with a foundation for expanding rule coverage, stewardship engagement, and governance oversight.