~2 minutes · 6 questions · Free

Is your data actually reliable?

Answer 6 questions and find out where your data infrastructure stands — and what to do about it.

You'll get a score, a tier assessment (At Risk / Needs Work / Strong), and tailored recommendations.

Question 1 of 617%

When two dashboards show the same business metric, how often do they agree?

They frequently disagree — we've given up reconcilingThey sometimes disagree and it takes real effort to explain whyThey usually agree, with occasional unexplained gapsThey always agree — we can explain every difference

Select an answer to continue.

What BayesIQ looks for in a real audit

When we begin a data quality engagement, we evaluate six dimensions — the same dimensions this assessment measures. The self-assessment gives you a directional view; an audit gives you the specifics.

Metric consistency

Do all your tools and queries agree on what a metric means and how to compute it?

Telemetry accuracy

Do your events fire correctly, with the right properties, in all conditions?

Pipeline observability

Do you know when something breaks, or do you find out from a broken dashboard?

Definition enforcement

Are your metric definitions written down and actually used, or just aspirational?

Incident history

How often has a data quality issue caused a visible problem?

Stakeholder trust

Do the people using your data trust it enough to make decisions from it?

See how a BayesIQ engagement works →

Common questions

Is this a real audit?: No — it's a self-assessment based on your answers to 6 questions. Think of it as a structured way to identify the highest-risk areas in your data infrastructure. A real audit involves examining your actual telemetry, pipelines, and metric definitions.
Who is this for?: Data leads, analytics engineers, and product leaders who are responsible for the reliability of business metrics and analytics pipelines. If you're not sure whether your data is trustworthy, this is a good place to start.
How is the score calculated?: Each answer is scored on a 0–3 scale based on data quality maturity. The total is converted to a percentage and mapped to one of three tiers: At Risk, Needs Work, or Strong.
What happens after I complete the assessment?: You'll see your score, tier, and up to 5 specific recommendations. You can optionally enter your email to receive the complete Data Quality Checklist that BayesIQ uses when starting new engagements.

Want a real answer, not a directional one?

A BayesIQ audit examines your actual telemetry, pipelines, and metric definitions — and gives you a severity-ranked fix plan in under two weeks.

Book a free data health check