Granicus Case Study: Building a Zero-Copy Data Mesh with Dremio’s Intelligent Semantic Optimization

The Challenge
Granicus (14 acquisitions, 5 countries) struggled with fragmented government data across 14+ sources: Salesforce CRM, EHQ MySQL, Matomo streams, GovD Oracle, Open Cities scraping, and more. Needed unified citizen analytics with regulatory compliance.

Technical Solution
•Nessie Catalog + Generative AI
•Iceberg metadata format with AWS S3 auto-reflections
•OpenSearch knowledge base for context-aware AI responses

Advanced Semantic Layer
•Complex multi-domain models with automated reflection optimization
•Query times: minutes → milliseconds through intelligent materialization

Dremio MCP NLP-to-SQL
•”Show housing meetings with >100 attendees last quarter” → Instant SQL
•Government-trained language models with optimal query generation

Dashboard Architecture
•Highcharts integration via Dremio REST APIs
•Intelligent caching for sub-second UI responses
•Real-time citizen engagement metrics

Zero-Copy Pipeline
•Staging → Business → Application layers (DBT + Iceberg)
•14+ sources unified without data movement

Live Demos:
•NLP query: “Find legislation about housing with citizen feedback >8”
•Real-time reflections optimization
•Highcharts dashboard with live government KPIs
•REST API caching performance comparison

Results:
•95% faster time-to-insight
•60% cost reduction through reflections
•300% increase in self-service adoption

Takeaways:
•Nessie + Iceberg configuration guide
•NLP-to-SQL with Dremio MCPs
•Highcharts-REST API integration patterns
•Reflections optimization playbook

Experience instant citizen insights through plain English queries powered by Dremio’s zero-copy architecture and intelligent semantic optimization.