Data quality work starts a step earlier than a dashboard: what is each system counting, which one is right, and has anybody written down which definition wins.
Frequently nobody has, and that is the finding rather than a failure. Settling it is the first deliverable.
What Data Quality Work Involves
Reconciliation. Take the two figures that disagree and trace both to source, row by row if that is what it takes. The output sorts the gap into timing differences, definitional differences and genuine errors, which need different responses.
Agreed definitions. Sales counts a deal at close, finance at invoice, operations at delivery. Each is defensible, and the argument exists because none is recorded where both sides can point at it.
Rules that actually run. A rule in a document is a wish. The same rule as a test that executes on every load and halts the pipeline is a control: uniqueness, referential integrity, ranges, and the business rules only somebody inside your company knows.
A named owner per dataset. One person who decides what the fields mean, which is what stops the whole thing unravelling within a year.
Duplicates, Which Are Always There
The same organisation sitting in the CRM three times under three spellings, each record carrying a fragment of the history. It comes up on nearly every engagement.
After that, dates stored as text. Then a field that quietly changed meaning when somebody repurposed it instead of adding a column, so any analysis crossing that date is wrong in a way nothing flags.
Delivered, Not Documented
We treat the two as one job. Data governance data quality checks run on every load and live in your repository, rather than in a framework nobody executes.
Data governance as a service here means tests running nightly, a definitions document with a name beside each entry, and a reconciliation you could hand an auditor. Everything is demonstrable in a running system at handover.
Being Irish registered, we keep those controls and their logs inside EU regions, and we give your compliance advisers the architecture detail they ask for.
How Engagements Start
A paid assessment first, usually two or three days, because a data management consultant who quotes before opening the systems is guessing. You get the reconciliation, the list of what is wrong, and a price against each fix.
Fixed price per deliverable after that. The definitions document and the tests sit in your repository from day one, which is what makes this a delivered control rather than an opinion in a slide deck.
Tell us which two numbers disagree and we will tell you what settling it takes, including the cases where a single afternoon of reconciliation answers the whole question.
Related Services
Where data arrives late or malformed to begin with, that is data engineering.
Where the corrected figures need to reach people, that is dashboards or Power BI on Microsoft estates. Where the question is what happens next rather than what is accurate, that is predictive analytics.