Data Integrity & Transformation

Are you moving systems?
Your numbers are at risk.

Every system migration is a moment where correct revenue can quietly become incorrect revenue — a field maps wrong, a calculation doesn't carry over, a pipeline drops rows nobody notices until reporting looks off.

Where it actually breaks

It's rarely the accounting theory. It's the pipeline.

In most organizations, the person who understands why a number should be calculated a certain way isn't the person writing the code that calculates it. The accountant knows the rule. The programmer builds the pipeline. And the handoff between them — from ETL, to transformation logic, to the final calculation — is where revenue quietly stops being correct.

It's usually not a dramatic failure. It's a source table that changed, a join that silently drops records, a rule that got implemented slightly differently than intended — because the accountant and the programmer were describing the same requirement in two different languages.

What I look at

Controlling the transition, not just surviving it.

System migrations

Moving platforms, ERPs, or data warehouses — making sure accounting logic survives the move intact, not just the raw data.

Pipeline & ETL validation

Tracing a number from source table through every transformation to the report — and confirming nothing changed meaning along the way.

The accountant-to-programmer handoff

Translating accounting requirements into specs a developer can build against correctly the first time — closing the gap where most errors start.

Reporting accuracy

Confirming that what leadership sees in a dashboard or report actually reconciles to the underlying data.

Planning a migration, or already mid-transition?

Either way, catching a broken pipeline before it hits reporting is a lot cheaper than catching it after.

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