Bad data has a price. Put a number on it.

Every silent failure burns engineering hours and stakeholder trust. Drag the sliders to estimate what data downtime costs your team per year — and what catching it in minutes is worth.

Data incidents per month6Stale tables, failed dbt runs, silent schema breaks — the average small team sees 4–10.Hours to detect + fix each one5hSilent failures are found days later by a confused stakeholder, then traced by hand.People relying on your dashboards12Everyone who pauses to ask 'is this number right?' when trust breaks.

Engineer firefighting$30,600/yr

Stakeholder time double-checking numbers$30,240/yr

Silent data failures cost you about

$60,840 /year

Avoidable by catching issues in minutes$36,504/yr

Vectornosis Pro, flat — no per-host math$3,588/yr

Your estimated net savings$32,916/yr

That is roughly a 10.2x return on the subscription — and the price never changes when your traffic spikes.

Book a data stack audit — see your real number

Estimates use loaded rates of $85/hr for data engineers and $70/hr for stakeholders, and assume fast detection avoids ~60% of incident cost. Your audit gives you exact numbers from your own warehouse.

No per-host math

Legacy observability bills by hosts, containers, spans, and custom metrics — then charges your busiest hour for the whole month. Vectornosis is one flat number.

No surprise invoice

Teams routinely report observability bills 3–10x their estimate. Your Vectornosis price is the price on the pricing page. That is the whole model.

No tuning tax

Most tools hand you a threshold editor and wish you luck. Vectornosis ships tuned for small BigQuery + dbt teams, so the first alert you get is one worth reading.

Want the real number instead of an estimate?

Book a data stack health audit