Data quality checks
Duplicate, missing and inconsistent records are found and flagged before they reach a customer, a report or a filing.
A checking system that runs over your records on a schedule and lists what is wrong: duplicates, missing fields, values that disagree between systems. It proposes a fix; a person decides whether to apply it.
No list price. It starts with a diagnostic at a fixed fee, and the build is quoted after it.
How it works
The pipeline, step by step.
- 01
The rules are written
What makes a record complete, what counts as a duplicate, which fields must agree across systems.
- 02
Records are read
From your CRM, policy, practice, accounting or order system, through approved connections.
- 03
Checks run on schedule
Daily, weekly or on each change, as you choose.
- 04
Findings are listed
Each with the record, the rule it failed and the evidence.
- 05
A fix is proposed
A merge, a corrected value, a missing field filled from a source you trust.
- 06
A person decides
Fixes are applied only after review, and every applied change is logged.
- 07
The trend is reported
Which rules fail most, and whether the list is getting shorter.
Connects to tools such as
- Salesforce
- HubSpot
- QuickBooks
- Xero
- Shopify
- PostgreSQL
- Google Sheets
These are examples. We confirm the method for each of your tools before we build.
Where a person approves
The points where the system stops and waits for a person.
- A person approves every merge and every correction before it is written.
- Rules are written with you and changed only on your instruction.
- Records you mark as protected are never changed by the system.
How it is measured
Named measures, scored on your own files before launch and after every change.
- Rule accuracy: findings checked against a reviewed sample for false flags and misses.
- Fix acceptance: the share of proposed fixes a reviewer applied unchanged.
- Open findings over time, as an operating measure.
How it is run
After launch: monitoring, updates and what you own.
- Monitoring on every run: failed reads, rule errors and unusual finding counts raise an alert.
- Rule changes are tested on a copy of your data before release.
- Handover: a runbook, a data map and code owned by the business.
What it will not do
Limits we set on purpose.
- It does not merge or delete a record on its own.
- It does not change a protected record.
- It does not guess a missing value without a source.
Sectors we build for
The business types this system is built for.
Questions
What does it check for?
Duplicates, missing fields, invalid formats and values that disagree between systems. The rules are yours; we write them down together.
Does it fix things on its own?
No. It proposes a fix with the evidence. A person applies it, and the change is logged with who, when and why.
How often does it run?
On the schedule you choose: daily, weekly or on every change to a record.
Which systems can it check?
Any we can connect: your CRM, policy or practice software, accounting and order systems. Cross-system checks compare the same record in each.
Talk to us about data quality checks
Fifteen minutes on a call is enough to tell whether it fits your work. If it does not, we say so.