Data management
Structuring and strengthening your data so it becomes truly usable.
- Data that supports business decisions
- A single source of reference
- Shared dashboards
Sound familiar?
- Your data is spread across several systems.
- Duplicates, inconsistent fields, different definitions from one team to another.
- Decisions rest on data whose reliability is not always clear.
- Every new report means reconciling the sources by hand.
What I bring
- A clear definition of what the data represents and what decisions it needs to support.
- A structure that reflects how teams actually work with information.
- Clear rules: who enters what, which source is the reference, how a correction goes back to the source.
- Reliable, shared dashboards instead of one-off extracts that differ from person to person.
How I work
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Clarify
What the data actually represents and what decisions it needs to support.
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Structure
So it reflects how teams use information, not just how it happened to be recorded.
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Govern and share
Clear rules for entry and correction, and dashboards that give a common view.
Governance rules, dashboards
LudoExplorer, a personal project built end to end
On my personal project LudoExplorer, focused on board game recommendations, I turned a large and inconsistent public dataset into a structured and enriched database, with a classification designed to match how users actually search for information. This structuring work came before any automation or AI functionality.
In detail
Context
Your organisation's data is spread across several systems, with duplicates, inconsistent fields and different definitions from one team to another. Decisions are then made using data whose reliability or definition is not always clear, and every new report requires manual work to reconcile the different sources.
My role
I start by clarifying what the data actually represents and what decisions it needs to support. I structure the data so that it reflects how teams actually work with and use information, not just how it happened to be recorded originally.
I put practical governance in place, with clear rules on who enters what, which source is the reference, where information should be stored and how a correction is traced back to the source rather than remaining isolated in a report. I also build dashboards that provide a reliable, shared view instead of one-off extracts that differ from person to person.
Your data exists, but its reliability, definition or origin is open to question?
Describe the problem and we will look together at how to make it genuinely usable.