Data governance: how to build a data foundation you can trust

Two reports, two figures. As long as there is no reliable single source of truth, every dashboard remains a source of debate. And anyone who wants to get started with AI soon notices that everything stands or falls with the data underneath.

In this guide, we set out how data governance lays a foundation that reporting, automation and AI can build on, based on the projects we run with our clients.

Data governance is the set of agreements, roles and processes that determine who is responsible for which data, how you safeguard quality and who may use what. It ensures that reporting, automation and AI draw from the same reliable source.

Data governance is therefore about people and agreements first, and only then about technology. A modern data platform without clear owners produces figures just as contradictory as a collection of loose Excel files.

Many organisations have more data than they use. Data is spread across systems that do not talk to each other, and each department reports in its own way. Who owns which data remains vague, while the AI Act raises the bar. And management is asking about AI, while the data foundation is not yet ready for it.

The steps below help you lay that foundation.

First map where your data is, how good its quality is, who uses it and which questions the business wants to answer with it. A maturity scan shows where you stand today and what needs attention first.

Appoint a data owner for each data domain, who decides on the data, and a data steward, who safeguards its quality day to day. Record which definitions you use, for example what an active customer is, and manage your master data centrally. That way everyone talks about the same figure.

With a modern data platform, you bring data from different sources together in one place, so that reporting and AI draw from the same source. Microsoft Fabric combines data integration, storage and analysis in one environment for this, with Power BI as the reporting layer.

With Power BI, you give the right people the right insight at the right time. Start from the decisions you want to support, and build the dashboards and KPIs around them. That is how Equans tracks its KPIs with Power BI, and ENTSO-E brought its HR data together in one ecosystem.

A dashboard only helps when people read and use it. With data and AI literacy programmes, employees learn to interpret figures, ask the right questions and work with reporting themselves.

With a reliable data foundation, you can go further. Automation and low-code turn insights into faster processes, and AI applications such as Copilot or AI agents work with data you can trust.

• Does the partner start with a maturity scan and your business questions, before a tool is chosen?

• Does the partner help you define roles, definitions and governance?

• Does the partner have experience with modern data platforms such as Microsoft Fabric and with Power BI?

• How does the partner make sure your people actually use the reporting?

• Can the partner build further towards automation and AI, within your governance?

Xylos is a Belgian family-owned tech company headquartered in Antwerp, with forty years of experience and more than 150 certified experts. Xylos is a Microsoft Solutions Partner for Cloud & AI Platforms and AI Business Solutions.

Xylos combines six building blocks depending on your situation: data strategy and governance, modern data platforms, dashboarding and insights, AI readiness, AI transformation and agentic AI, and data and AI literacy. A project starts with a maturity scan, then lays down the data foundation and governance, turns data into insights and use cases, and takes AI to production. After delivery, Xylos keeps managing and adjusting the environment.

You see results after every step, so you decide yourself how far you go.

In an exploratory conversation, our experts map your data environment and sketch the first outlines of your path to reliable insights.