Perfect Data Cloud is built for small to mid-sized organizations that need repeatable data quality monitoring: create rules, schedule scans, and notify the right owners before issues hit reporting.
Everything you need to operationalize monitoring without heavy lift.
Define “bad data” with rules (typically SQL/query-based) that surface exceptions clearly and repeatedly.
Run scans on a cadence that matches your operational needs—hourly, nightly, or aligned to reporting cutoffs.
Send alerts to the right owners so issues get resolved quickly—and don’t keep recurring.
Organize rules by team or domain. Assign roles for analysts, fixers, and stakeholders.
Track whether error counts are improving over time. Turn repeated breaks into measurable progress.
Start faster with recommended rules, then customize and expand as your monitoring program matures.
Perfect Data Cloud is designed around a simple operational loop: define checks, run them automatically, and notify owners.
Perfect Data Cloud is typically a fit when you want speed, simplicity, and an essential feature set.
A quick directional guide. (Your actual offering details may vary—adjust as needed.)
Common questions about Perfect Data Cloud.
Perfect Data is typically used against reporting databases and data warehouses. If you have mixed sources, we’ll help you determine the best approach during onboarding.
Rules are usually expressed as queries that return the “exception rows” (bad data). The platform runs rules on a schedule and tracks outcomes over time.
Yes. Most teams begin with a handful of high-impact rules tied to critical reports, then expand their library as they build confidence.
If you require SSO, complex user/group management, or you anticipate many teams and hundreds of users, Cloud Enterprise is typically a better fit.
We’ll map your first rules, suggest a rollout plan, and confirm whether Cloud or Enterprise is the right fit.