Data governance

A data governance framework short enough that people follow it, with a named owner for each set of data your decisions depend on.

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What a framework covers

The work is sized to the company and to the state its data is already in. The parts below are what a framework tends to touch.

Ownership: Who owns each dataset that decisions rest on, and who to ask when a number looks wrong.
Agreed definitions: A shared meaning for the terms that teams argue over, written down so the argument stops.
Rules that matter: The small set of rules worth enforcing, chosen because breaking one causes a real problem.
Access and sensitivity: Who may see which data, and how the more sensitive sets are handled and shared.
Quality checks: Simple tests that catch the errors most likely to mislead a decision, run where the data lives.
A written policy: A data governance policy short enough that the people bound by it will read it.
Keeping it current: A light way to review the framework as the data and the company change, without a committee that meets forever.

A framework people follow

Most governance efforts go the same way. A long policy gets written to anticipate every case, and then it sits in a shared folder that nobody opens. The version that works is short. It starts from the data the company really acts on and gives each set an owner, and it keeps only the handful of rules that are worth the trouble of enforcing.

Ownership has to sit with named people. When a reported figure looks off, one person should be accountable for it and have the standing to put it right. A framework that stays this small tends to stay in use after the consultants have gone.

Tevelis also builds the pipelines and infrastructure that data runs through, so the framework is written with that engineering in view. Each quality check is designed to run on your own systems, or on a copy under your control, which means the policy describes checks that actually happen.

How to start

The brief

Tell Amos which datasets carry your decisions and where they sit today. Point to any figures that have misled you before, and to rules you already try to keep.

How it runs

An engagement usually opens with a small piece of work on your own data, so you can weigh it before going further. Your data stays in your hands throughout.

Who does the work

For more than two decades Amos Weiskopf has built software and data systems for companies and governments, which keeps the framework he writes close to how data is really gathered and used.

Questions buyers ask

What is data governance?

It is the rules and ownership that decide who is responsible for your most important data and how accurate it has to be before anyone acts on it. The version that holds up is short and gets followed.

What is the difference between a framework and a policy?

The framework is the working arrangement: who owns which data and how it is kept accurate. The policy is the written document that states the rules, and it only works if it is short enough to be read.

How long does a data governance framework take to set up?

That turns on how many datasets carry weight and what condition they are in. The work begins with the few that matter most, and the timetable is settled in the brief.

What does data governance consulting cost?

The price depends on how many datasets are involved and how much they need, and it is set once your written brief is in. Nothing is fixed ahead of that.

Do we need a governance committee?

Usually not a large one. Responsibility tends to hold better with a few named owners than with a standing committee that meets to review rules nobody reads.

Can the checks run on our own systems?

Yes. The quality checks are made to run on your data where it sits, or on a copy you hold yourself. If any of it might go to an outside provider, that is agreed with you first.

Engagements by written brief.

Work begins from a documented problem statement, not a sales call.

Write a brief Or book a meeting