Data Cleaning & Quality Remediation
Fix the records your team keeps correcting by hand.
When duplicate customers, inconsistent fields or disconnected records make reports hard to trust, start with one agreed dataset for one defined business use.
This opens Cal.com for an initial Discovery & Scoping Session. Bring a description of the issue and the outcome you need. Keep customer records and credentials out of the booking form.
Where it hurts
Where is the data getting in the way?
Duplicate records
The same customer appears twice in a report, and your team has to decide which entry to count.
Inconsistent fields
Teams use different status labels or formats, so the same jobs get grouped differently.
Disconnected customer information
An account in one export is hard to match to the right service record in another.
Unreliable operational reporting
Two reports disagree, and your team can’t tell which differences come from the underlying records.
Scope
Bring one dataset and one business use.
Data cleaning and cleansing services fit when you know which records are causing trouble and what those records need to support. Bring a description of the source, affected fields, intended use and the person who can approve cleanup rules.
This is an export-only project. A migration, live-system update, dashboard rebuild or ongoing monitoring needs a separate scope.
How a scoped cleanup works
- Agree on the business use, dataset, fields and what a usable output looks like.
- Profile an agreed copy and identify duplicates, inconsistent fields, gaps and conflicts.
- Define rules for matching records, correcting fields and reconciling the output with the input.
- Review representative examples and get your data owner’s approval before applying the rules.
- Apply the approved corrections to a working copy.
- Check the output against the agreed criteria and document unresolved exceptions.
- Hand over the revised dataset, change summary, exception log and validation evidence.
Deliverables
What you take away
Revised dataset
An exported copy in the agreed format for the defined business use.
Change summary
The approved rules and a record of what changed.
Exception log
Unresolved conflicts, missing values or uncertain matches, with the evidence or decision needed.
Validation evidence
The checks performed, their results and any limitations to review at handoff.
Synthetic example
See how a cleanup decision is made.
These are fictional records for a weekly customer report. The example illustrates a handoff and does not describe client work.
| Source | Customer | Status | Region |
|---|---|---|---|
| A-17 | C-100 | ACTIVE | North |
| B-08 | C-100 | active | West |
| A-18 | C-101 | active | South |
Exception E-01: C-100 region conflict
The owner approves normalizing the status to “Active.” C-100 stays under review until the owner checks the authoritative account record, confirms North and approves one row for the reporting copy. Without approval the conflict would stay open and the rows would stay separate.
After: approved reporting copy
- C-100: Active, North. Source references A-17 and B-08.
- C-101: Active, South. Source reference A-18.
Validation: three source rows reconcile to two output rows with one approved consolidation. The source records stay in place.
Choose your entry point
Start where the problem is clear.
A defined cleanup is a Build / Rescue project. It includes profiling the agreed dataset and planning its cleanup rules, and can end at handoff.
If you’re still tracing the cause across workflows, consider the Business Process & Technology Assessment. A Pacisci Game Plan can be scoped separately when a broader execution roadmap is needed.
For ongoing connected workflows, explore AXIS, Pacisci’s managed operating solution powered by its AIOS architecture. See Data & Analytics for reporting and fractional data support, or Build & Integrate for system integration.
FAQ
Questions before you scope a project
- Do we need a separate assessment first?
- No. If you know which dataset needs work and how you’ll use it, start with direct project scoping.
- Can you work with our system or file format?
- Tell us how you store the records and what you need back. We’ll confirm whether the format, scope and access requirements fit before agreeing to a project.
- Will you merge duplicates automatically or edit our live system?
- This offer delivers an export from an agreed working copy. Your source records stay in place, and uncertain matches go to your data owner for review.
- What if two sources disagree?
- We use the rules agreed with your data owner. If the evidence is insufficient, we flag the conflict and show what decision is needed.
- Will this fix our reporting?
- We can agree on checks for a defined reporting use. Report logic, source coverage and workflow issues may require separate work.
- What should we share for the first call?
- Describe the source, the problem and the intended output. Wait until access and transfer requirements are agreed before sharing records.