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DTSTAMP:20260520T225950Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-edw2026.data
 versity.net/sessionPop.cfm?confid=165&proposalid=16467\nOrganizations like 
 ours often launch data governance programs with a clear vision, only to fin
 d that measuring data quality consistently is harder than expected. At the 
 City of Ontario, California, we faced the same issues many teams encounter:
  scattered spreadsheets, inconsistent definitions, and manual checks that m
 ade it tough to track trends or demonstrate impact.\n\nThis session shares 
 how we addressed those challenges by designing and automating agency KPIs a
 nd Data Quality Metrics that connect business rules, system validations, an
 d workflow monitoring into a repeatable pipeline. We&rsquo;ll walk through 
 how we standardized KPIs, automated calculations across systems, and delive
 red dashboards that both executives and operational teams actively use&mdas
 h;along with the data quality measures that reveal the true health of the d
 ata.\n\nWe&rsquo;ll highlight the technical patterns (Snowflake SQL, tasks,
  quality rules, metadata tables), the governance processes (ownership, thre
 sholds, issue lifecycle), and the lessons learned implementing this solutio
 n in a large municipal environment with diverse data sources.\n\n
 How we identified gaps in our early data governance efforts and turned them
  into a roadmap for quality measurement\n
 The framework we built to automate KPIs and data quality metrics across mul
 tiple municipal systems\n
 Technical patterns using Snowflake SQL, tasks, metadata tables, and rule-ba
 sed validations\n
 How standardized business logic, definitions, and workflows enabled consist
 ent KPI reporting\n
 Governance practices that support sustained adoption: ownership, thresholds
 , and data issue lifecycle management\n
 Lessons learned implementing automated data quality monitoring in a large, 
 operational city environment\n\n
DTSTART:20260505T101500
SUMMARY:The Automation Path: KPIs and Quality Metrics for Real-World Munici
 pal Data Governance
DTEND:20260505T105959
LOCATION: See Description
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