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Data Quality

The Data Quality helps foster trust in data across the organization. Our mission is to proactively manage and monitor data quality, enabling confident decisions, reliable reporting, and wider adoption of institutional data assets

What We Enable

The Data Quality team partners across the organization to improve the reliability and usability of data. Our focus is on building shared ownership of data quality through transparent monitoring, proactive alerts, and clear expectations.

We enable:

  • Alignment on Data Quality Expectations: Collaborating with stakeholders to define what “good” looks like for key data assets
  • Business Rule Definition: Helping domain experts define meaningful validation and reconciliation logic
  • Automated Data Monitoring: Developing proactive checks to detect anomalies in production data
  • Quality Reporting & Visibility: Delivering dashboards and summaries to track trends and identify risk
  • Issue Notification: Notifying the right people and supporting them in interpreting and acting on data issues

How We Do It

We deliver data quality enablement through collaborative definition, automated checks, and structured reporting.

Stakeholder Collaboration

We partner with business and technical stakeholders to:

  • Define quality expectations and business rules
  • Align priorities based on impact, visibility, and urgency
  • Establish shared ownership of data reliability

Rule Definition & Monitoring

We help teams codify their quality logic into executable rules:

  • Define validations, reconciliations, and threshold-based logic
  • Implement automated data checks that run on production pipelines
  • Monitor for completeness, consistency, timeliness, and validity

Issue Detection & Alerting

We surface problems early, where they can be resolved quickly:

  • Detect anomalies through automated checks
  • Notify appropriate data owners via structured alerting
  • Provide context to help teams take appropriate action

Quality Reporting

We make data quality visible and measurable:

  • Dashboards and trend reports that highlight quality metrics
  • Summaries of rule performance and issue frequency
  • Views by domain, source system, or business unit

For any further discussions or partnership opportunities for data quality, please contact Van Ngo (VanJNgo at ucla.edu)