The Missing Layer to Observability
Continuous data validation that proves your data is correct, not just delivered.
The Challenge
Data breaks quietly, then shows up loudly.
Row counts and job status can look fine while data is incomplete, incorrect, late, or drifting. Teams lose hours in war rooms trying to figure out what changed and who owns the fix.
Common pain points:
- Silent data drift after logic or schema changes
- Partial loads, missed refreshes, and broken dependencies
- Source to target mismatches after ETL/ELT
- Broken metrics and dashboards discovered by stakeholders
- Slow root cause analysis across multiple tools and teams
Data Observability You Can Trust
QuerySurge adds the missing layer to observability: automated data validation across sources, pipelines, warehouses, and BI, so you catch issues early and resolve them fast.
The QuerySurge solution
QuerySurge enables data observability by continuously validating data correctness at scale.
Instead of guessing whether data is trustworthy, QuerySurge proves it with automated, repeatable tests that run where your data lives and wherever it moves.
What you get:
- Early detection before bad data reaches analytics and operations
- Source to target validation that confirms transformations and business rules
- Fast diagnosis with variance detail, trends, and historical context
- Operational controls that fit directly into DataOps and governance programs
How it works
1) Connect to your environment
QuerySurge connects to your sources, lakes, data warehouses, data marts, and BI layers through flexible data stores and agents.
2) Build validations that matter
Create automated tests for:
- Reconciliation (source vs target, stage vs warehouse, mart vs BI)
- Transformation logic (joins, filters, aggregations, derived fields)
- Business rules (thresholds, referential integrity, completeness)
3) Automate runs in your workflow
Run test suites:
- On schedules (hourly, daily, per load)
- Triggered by pipelines and orchestration tools
- From CI/CD using the QuerySurge REST API and webhooks
4) Act on results immediately
Get pass/fail visibility, detailed variance, and alerts routed to the right team, with the context needed to fix issues fast.
Key Capabilities
Function |
Details |
|---|---|
Continuous Validation across the lifecycle |
Validate data at every checkpoint:
|
Automation and Integration |
|
Enterprise Scale and Governance |
|
Results Analytics and Trending |
|
Where QuerySurge fits in a data observability stack
Monitoring shows you which jobs ran. QuerySurge tells you whether the data is right. Pipeline and infrastructure monitoring are necessary, but they do not confirm correctness. QuerySurge complements observability platforms by providing the data validation layer that proves trust.
Common use cases
- Production data quality controls for critical datasets
- Cloud migrations and modernization (prove parity and catch drift)
- Data warehouse and lakehouse reconciliation
- Release confidence for dbt, SQL, ETL/ELT changes
- BI trust: detect broken metrics before stakeholders do
Outcomes
- Faster detection of data defects before they impact the business
- Reduced incident volume and shorter root cause cycles
- Higher confidence in dashboards, analytics, and operational reporting
- Stronger governance with automated, repeatable controls
- Scalable validation that replaces manual SQL spot checks
Make data trust measurable.
Bring continuous data validation to your observability strategy with QuerySurge.
