Data owners and stewards
A visible control loop for identifying, prioritising and resolving data quality issues.
Turn data quality from a clean-up project into an operating discipline.
A control-centre product designed to detect duplicates, missing values, stale records, invalid relationships and reporting risks, then route remediation work with visible ownership and evidence.
Designed for
Teams that need trusted operational data before automation, reporting or migration.
Continuous data quality operations for Dataverse and connected business data.
CRM and Dataverse administrators
A visible control loop for identifying, prioritising and resolving data quality issues.
Operations managers
A visible control loop for identifying, prioritising and resolving data quality issues.
Reporting and migration teams
A visible control loop for identifying, prioritising and resolving data quality issues.
Governed delivery flow
From approved need to release evidence.
Choose a stage to see how the target experience works.
01
01 · Understand
Profile
Measure completeness, validity, duplication and freshness across agreed data domains.
02
02 · Controls
Detect
Run transparent rules and create prioritised quality findings.
03
03 · Ownership
Assign
Route issues to the right data owner or operational queue.
04
04 · Action
Remediate
Correct records through controlled workflows and approved tools.
05
05 · Assurance
Verify
Re-run controls and retain evidence that the issue was resolved.
06
06 · Prevention
Improve
Use trends to improve forms, integrations, rules and ownership.
Explore the product
Go deeper without losing the big picture.
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Quality controls
Transparent rules for the issues that undermine operational confidence.
Remediation operations
Move findings into controlled queues with ownership and evidence.
Reporting and insight
Show where quality is improving and where risk is accumulating.
Governance
Define the ownership and change controls behind quality rules.
Reference architecture
A Microsoft-stack direction for profiling, controls, workflow and analytics.
Roadmap
Productisation will focus on repeatable controls and customer-specific extensibility.
Pilot approach
Start with one important data domain and a small set of measurable controls.
Frequently asked questions
Clear boundaries for the product proposition.
Data quality assessment
Create an operating model for trusted data.
Tell us which data domains, business systems and reporting risks need stronger controls.