Automatically deploy relevant tests & monitors

Build a robust testing and monitoring strategy with Scout AI. Scout combines business context, proven testing best practices, and a deep understanding of your code, lineage and logs to recommend and deploy a best-in-class testing setup.

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You know testing matters, but doing it right is hard.

As data stacks grow in complexity, defining the right tests can become overwhelming. Most teams don’t know where to start, rely on generic templates, or end up firefighting issues downstream. Scout recommends the most relevant tests & monitors for your use case with all the context.

Testing strategy
What to test
How tests are added
Context awareness
Alert Noise

With Scout

Automatically derived from lineage, metadata, and usage context
Contextual suggestions tailored to your stack, test only what's relevant
Suggested and deployed
as PR’s in dbt
Ingest business rules, data products and custom prompts
Fewer, smarter alerts
based on criticality

Manually

Depends on individual expertise; often inconsistent or undocumented
Generic templates (e.g. not null, unique) applied uniformly, risk of overtesting
Written manually
Typically unaware of broader usage or downstream impact
Higher risk of alert fatigue from non-actionable failures

Scout makes everyone a testing expert

Data Lineage

Out-of-the-box testing best practices aligned with analytics engineering workflows

Scout adapts to your business and is integrated with the tools you already work with.

Testing best practices baked in from day one

Choose from one of our recommended testing strategies (we wrote the guide about it!) or tailor your own strategy.

Deeply integrated with dbt & SQLMesh

Push tests directly into your transformation workflows. Scout opens pull requests in dbt & SQLMesh, so tests live where your team works.

Deploy tests & monitors in the tools you use. Bring everything together with SYNQ

Monitor all your data controls in one unified dashboard that combines your SYNQ monitors with data controls from dbt, SQLMesh, Airflow and much more.

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Benefits of a robust testing setup

Leveling up your testing on par with top data teams brings results.

Catch All Data Issues
58% of data practitioners rate poor data quality as a top problem. It doesn't have to be so (Aiven case study)
Minimize Alert Fatigue
Teams using SYNQ have gone from dozens of daily alerts to just a few targeted each week (Dext case study)
Productivity Gain
Data teams spend an avg. or 20% of their time working reactively, firefighting and debugging issues. Get time back (Insatbee case study)

A fully integrated data observability platform

Our integrations make it easy to work with all the platforms and applications you want to use. We’re proud to be a fully integrated platform for data quality.

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