The Product Analytics Layer for the Modern Data Stack.
Stop building custom SQL dashboards for every PM question. Mitzu acts as a self-service interface on top of your existing warehouse tables, governed by your dbt metrics.
Modern Data Stack Architecture
Zero data movement, full SQL transparency
Snowflake
BigQuery
DatabricksTrusted by data teams worldwide
The Data Engineer Pillars
Built to address the Data Team's biggest concerns: governance, maintenance, and transparency.
Governance First
Define your metrics once in code (dbt/YAML). Mitzu inherits your definitions, ensuring that 'Active User' means the same thing in the dashboard as it does in the database.
Zero ETL Maintenance
Forget 'Reverse ETL' pipelines that break every Tuesday. Mitzu reads directly from your views, so there's no synchronization lag or pipeline debt.
Transparent SQL
We don't hide the logic. Inspect, audit, and copy the raw SQL generated by any Mitzu chart to verify accuracy or optimize query performance.
Get Ad-Hoc Tickets Off Your Back.
Empower PMs to answer their own questions about funnels and retention. You build the data models; they build the insights.
- PMs self-serve on approved metrics and tables
- No SQL knowledge required for business users
- Data team focuses on modeling, not dashboards
- Faster time-to-insight for the whole organization
Ad-Hoc Data Requests
Before vs After Mitzu
Inherited Security Permissions.
Don't manage a second layer of users. Mitzu respects your warehouse's Role-Based Access Control (RBAC) and Row-Level Security (RLS) policies.
- Automatic role mapping from Snowflake/BigQuery
- PII masking inherited from warehouse policies
- No duplicate user management
- Audit logs for compliance requirements
Role Mapping Configuration
Snowflake Role → Mitzu Group
Query Efficiently.
Worried about compute costs? Mitzu uses incremental caching and optimized aggregations to ensure self-service doesn't blow up your Snowflake credits.
- Incremental caching reduces redundant queries
- Query timeouts and resource limits per user
- Optimized aggregations for common patterns
- Real-time cost monitoring dashboard
Query Efficiency
Cached vs Fresh Queries - Last 7 Days
$2.4K
Saved this month
1.2s
Avg response time
The Engineer Flow
Get your team up and running in under a day. No complex migrations required.
Connect
Create a Read-Only Service User in your Warehouse. Mitzu never writes to your data—only reads.
Sync
Connect your dbt repository to automatically sync metric definitions and semantic models.
Govern
Whitelist the tables PMs are allowed to see. Control access at the schema, table, or column level.
80%
Reduction in Ad-Hoc Tickets
0
Data Pipelines to Maintain
100%
SQL Transparency
Frequently Asked Questions
Everything data engineers need to know about Mitzu.
Ready to empower your data stack?
Stop building custom dashboards. Start enabling self-service analytics on your existing warehouse.