Data
Atlas
6 d → 0 d of manual consolidation
- Field
- Data
- Result
- 6 d → 0 d
- Role
- Audit, data engineering, dashboard
01.Context
A finance team consolidated figures from its sales, accounting and CRM tools every month, in a chain of hand-linked spreadsheets.
02.The problem
Six days of copy-and-paste at every close, gaps nobody could explain, and figures that arrived too late to act on.
6 d
of manual consolidation
03.The approach
Map the figures that matter
An inventory of sources, of the metrics leadership actually reads, and of the formulas hidden in the spreadsheets.
Automate the collection
Pipelines that extract, clean and reconcile data from each tool every night, with no human in the loop.
One source of truth
A data warehouse where every metric has a written definition and a single calculation, tested at each load.
A dashboard that warns
Closing figures are ready on day one, with alerts whenever a gap looks unusual.
04.Measured result
Before : 6 dAfter : 0 d
of manual consolidation
- manual consolidation
- −100%
- of manual work removed
- 6 d
05.Stack
- Python
- PostgreSQL
- dbt
- Metabase
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