The problem nobody sees (until it hurts)
Every company accumulates data faster than it accumulates understanding of that data. The result creeps in slowly: the same customer registered three times, reports that never agree with each other, systems that don't talk, and that simple question — "how many active customers do we have?" — with four different answers depending on who you ask.
Data Administration is the discipline that fixes this at the cause, not the symptom. It means treating data as the corporate asset it is: with an owner, a standardized name, a documented meaning and quality rules.
How we work
Our focus is less infrastructure, more business: we don't just look after the database — we look after the meaning of the data. We map what exists, standardize naming, build the data dictionary and establish processes so order survives everyday life. With AI as an assistant, what used to take months of manual discovery now takes weeks — assisted reverse engineering, generated-and-reviewed documentation, inconsistencies detected automatically.
Who it's for
Companies that have already felt the cost of disorder: system projects blowing past deadlines because nobody knows where the data lives, system mergers, audits, data-protection compliance, or simply a new BI that exposed the mess. If your reports don't match, the problem is almost never the report.
What you get
- A diagnosis of your data's current state (the honest X-ray)
- Data dictionary: every table and column with its meaning documented
- Naming standards and best practices your team can actually apply
- A corporate data model — the single photograph of your business
- Detection and correction plan for redundancies and inconsistencies
- Governance processes so order holds without depending on heroes