We fix it and keep it fixed
A one-time manual cleanup decays the moment new bad data starts flowing in. We pair the cleanup with validation rules and constraints — at the form, at the import, at the database — so the data stays clean.
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Decisions are only as good as the data behind them.
Duplicate customers. Inventory counts that don't match the shelf. A mailing list with three versions of the same address. Reports that disagree depending on who ran them. Bad data quietly costs you money and trust. We clean it, deduplicate it, validate it, and put guardrails in place so it stays clean.
Based in Chattanooga, serving the Tennessee Valley and remote. Fixed-bid cleanup, plus optional ongoing guardrails.
What our data quality service includes
Data quality work is two halves: a one-time cleanup of the mess you have, and guardrails so it doesn't come back. Here's what's involved.
- Data audit — profiling your records to find duplicates, gaps, and inconsistencies
- Deduplication with sensible matching rules (fuzzy matching on names, addresses, etc.)
- Standardization — consistent formats for addresses, phone numbers, names, dates
- Validation against authoritative sources where possible (address verification, etc.)
- Merging records across systems that hold the same entity differently
- Cleanup of customer lists, inventory, product catalogs, and financial data
- Validation rules and constraints so bad data can't get entered going forward
- An optional ongoing monitoring/cleanup routine
Why us
Why businesses choose us for data quality work
We come at data quality as developers, so we don't just clean the current mess by hand — we build the rules and constraints that keep it clean, and we automate the cleanup so it's repeatable instead of a one-time heroic effort that decays.
Sensible deduplication
Naive dedup either misses obvious duplicates or merges records that shouldn't be. We tune matching rules to your data and let you review the uncertain matches, so the merge is safe.
Repeatable, not heroic
We script the cleanup so it can be re-run. If you onboard a messy new dataset later, the same process cleans it — no starting from scratch.
Works across your systems
Data quality problems usually span tools — the CRM, the accounting system, the spreadsheet. We can clean and reconcile across all of them, not just one.
How it works
How a data quality engagement runs
Profile the data, agree on the rules, clean it safely, and add guardrails.
- 1
1. Data audit
We profile your data and report what we find — how many duplicates, how many invalid records, where the inconsistencies are, and what cleaning it is worth.
- 2
2. Rules + plan
We agree on matching rules, standard formats, and what counts as valid, then quote a fixed price for the cleanup.
- 3
3. Clean safely
We work on a copy first, let you review uncertain merges, and apply the cleanup only once you've signed off — so nothing valuable gets lost.
- 4
4. Guardrails
We add validation at the points data enters your systems so the mess doesn't rebuild, and optionally set up an ongoing monitoring routine.
Outcomes
What you get out of it
Clean data makes everything downstream better — marketing, reporting, operations, and the decisions you base on them.
Reports you can trust
When the data is clean and consistent, your reports agree with each other and with reality — so you can actually act on them.
Less wasted spend
No more mailing the same customer three times, ordering inventory you already have, or chasing leads that are duplicates.
Better customer experience
One accurate record per customer means no duplicate emails, no wrong addresses, no 'didn't you already have my info.'
Data that stays clean
Validation guardrails mean the cleanup holds instead of decaying back into a mess within months.
Data quality management — FAQ
Questions people ask before we start.
A one-time cleanup typically runs $2,500–$10,000 depending on the size and messiness of the data and how many systems it spans. Adding ongoing guardrails and monitoring is a smaller add-on. We quote fixed-bid after the data audit.
Where we work
Data quality management for businesses across the Tennessee Valley.
We’re based in Chattanooga and work with small businesses across the region — Hixson, East Ridge, Red Bank, Soddy-Daisy, Signal Mountain, Ooltewah, Collegedale, Cleveland TN, and Dalton GA — plus remote clients anywhere.
See the cities we serveRelated services
Often paired with data quality management.
Database design
PostgreSQL schemas, query optimization, and indexing strategy — the work that makes slow apps fast and tangled data clean.
Learn moreCustom software
Internal tools, dashboards, and focused web apps built around how your business actually works.
Learn moreSoftware integration
Making your tools talk to each other — APIs, webhooks, and custom connectors between the systems you depend on.
Learn moreDon't trust your own reports?
Free 30-minute call. Tell us where the data feels wrong and we'll tell you whether a cleanup is worth it and what it would take.