Operations & data
One workspace for data that used to live in forty spreadsheets
Data Manager takes messy exports from every system a business runs on, cleans and matches them, and pushes reliable records back out on a schedule.
- Type
- Internal platform
- Scope
- Data model, pipelines, UI
- Status
- In daily use
The challenge
What needed solving
Critical records were spread across CRM exports, finance files and supplier feeds, each with its own column names and duplicate entries.
Reporting depended on one person's spreadsheet, and nobody could say with confidence which version of a record was correct.
The build
What we made
Flexible ingestion
CSV, spreadsheet and API sources mapped to a shared schema, with column mapping saved and reused on every run.
Cleaning and validation
Rules catch bad formats, missing fields and outliers before anything is written, with everything flagged for review rather than silently dropped.
Deduplication and matching
Fuzzy matching merges records across sources into one master entity, keeping full lineage back to each original row.
Scheduled exports
Clean data pushed back into downstream tools automatically, so teams work from the same numbers every morning.
Outcome
Where it landed
- Manual spreadsheet reconciliation replaced by a scheduled pipeline
- Duplicate records collapsed into a single trusted master view
- Data issues surfaced for review instead of discovered in a report
- Reporting no longer depends on one person's file
Got a build like this in mind?
Tell us what you're trying to ship and we'll tell you honestly what it takes.