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Data Governance

Clear responsibilities and rules for enterprise data

We build a data management framework that clarifies where your data comes from, its quality, how it is used and who is responsible for it.

Get in touchHow we work
Isometric illustration: a padlocked shield at the centre, surrounded by databases, servers, charts and a "Governance Board" dashboard, linked by blue and purple light lines.

  • 01 /

    A known and traceable data estate

    We map what data is available, where it originates and which processes use it. Identifying shared definitions and data sources helps avoid conflicting interpretations.

  • 02 /

    Data quality and clear ownership

    We define data quality rules and assign the related responsibilities. Handling discrepancies can become an organised process and can strengthen the foundation for reports, analytics and AI solutions.

  • 03 /

    Controlled access and use

    We align access rights and compliance requirements with how the data is used. Clear rules support data sharing and risk management across the company.

Two engineers seen from behind reviewing a system architecture diagram on a dark screen; the protected nodes glow orange.

Our approach

We shape the Data Governance framework together with business users and IT. We start with the most important data and problems so that the rules work in day-to-day operations. We introduce the ownership model, quality requirements and control processes together.

Working together

  1. 01Mapping the data estate and its problems

    We review the main data sources, how data is used and current quality issues. We select the first data domain to address and the business areas involved.

  2. 02Defining rules and responsibilities

    We agree on data definitions, quality requirements and access rules. We define who is responsible for the data and for handling discrepancies.

  3. 03Rollout in a selected data domain

    We apply the framework to the selected data and processes. We check how usable the rules are and how data quality issues are handled.

  4. 04Review and expansion

    We evaluate the experience and refine the operating model. We gradually extend proven practices to further data domains.

Contact us

Phone:
+36 1 611 0462
Email:
info@blackbelt.hu
What are you interested in?