From launchpad to orbit: making data governance great again

Let’s be honest, data governance doesn’t exactly set pulses racing. ‘Metadata’, ‘classification schemas’ and ‘access controls’ can sound like boring bureaucracy.

Yet, data governance is having a moment. What was once boring is now mission-critical in an age when AI and advanced analytics are taking the lead. Suddenly, the stakes are higher than ever. Modern governance isn’t just about compliance checkboxes, it’s a strategic enabler for an AI-powered future.

Good governance benefits everyone. From the CIO worried about data risks, to IT admins craving clarity, or analysts seeking trustworthy data, data governance is a launchpad for safer collaboration and smarter decisions.

Many enterprises today are hoping technology alone, with tools like Microsoft Purview, will magically solve their compliance headaches and governance gaps. Don’t get me wrong; it is a stellar platform. It simplifies data discovery, cataloguing, classification, and even compliance monitoring. But, Purview is not a strategy, it’s an enabler. Expecting it to solve fundamental governance challenges is like expecting a high-tech guidance system to launch a rocket without engineers first defining the flight path and calibrating the controls. You will get navigable chaos.

The illusion of instant governance

Organisations today face enormous pressure from escalating regulatory demands, heightened privacy expectations, and relentless AI agents scanning every corner of their data. It's tempting to reach for quick fixes, plugging in tools like Purview, flipping on auto-classification, enabling DLP rules, and mistakenly believing this equates to effective governance.

Sure, a 'vanilla' implementation of Purview will give you valuable capabilities out-of-the-box, such as automated data discovery, initial classification, and basic compliance monitoring. However, without clearly defined owners, comprehensive policies, and structured processes in place, Purview can become little more than a flashlight in a cluttered launch bay filled with forgotten rocket parts:

• Data quality still matters – ‘Garbage in, garbage out’ remains truer than ever. Purview won’t magically clean up messy, duplicate, or outdated data. Without processes to improve data quality, you are just cataloguing a mess.

• Classification needs clarity – Yes, Purview can auto-tag and classify data, but it needs to know your rules. It works best when guided by a thoughtful classification schema and labelling taxonomy you have pre-defined. If you haven’t decided what ‘Confidential’ vs ‘Public’ means for your business, the tool is guessing in the dark.

• Security and access need strategy – A robust tool amplifies your security posture only if you have defined clear access control policies and roles.

• No tool can fix unclear ownership – Without clearly defined data owners and stewards, governance becomes a blame game or, worse, a forgotten chore. Purview can show you data inventories, but it can’t assign accountability by itself.

Governance isn’t just about tooling; it’s about intentional design

Before you configure Purview (or any tool), you need a basic data governance strategy to act as an implementation framework. Not a 100-page manifesto, just a clear, actionable playbook. This document should clearly define the essentials:

• Data quality standards – what does ‘good’ data look like, and how do we fix it when it’s not?

• Security and access control – who owns the data, who should see what, and how do we keep sensitive data locked down?

• Classification and cataloguing – how do we label and organise information so it’s discoverable and protected?

• Retention guidelines – how long do we keep different types of information?

A practical governance framework doesn’t need to be heavy or academic. It does not have to be complex either, in fact, the best frameworks are simple, pragmatic, and built to evolve. Think of it as a flight plan - the artefacts you define here become the configuration inputs for Purview. By defining these governance building blocks upfront, you are essentially teaching Purview what matters to your business.

Minimum Viable Governance (MVG): progress over perfection

A phased approach with clear milestones and quick wins beats an overwhelming big-bang project. It’s about progress, not perfection on day one. What you need is Minimum Viable Governance, just enough governance to establish a solid foundation and momentum. just enough structure to:

• Protect sensitive data (so you are not the next data breach headline)

• Enable safe collaboration (so your team can share data without constant worry)

• Support AI use cases (your data is prepped and fit for AI consumption)

• Pass audits without panic (regulators are satisfied and you’re not scrambling)

With MVG, you start small - identify a few key policies or processes that address your biggest risks or needs. Maybe that is defining a basic classification scheme and applying labels to your top 10 sensitive data sets. Maybe it is drafting a simple data ownership chart for your most critical systems. Maybe it is enabling audit logging and DLP monitoring on your email and SharePoint as a quick win. Define your key artifacts, implement them in a focused scope, and then use Purview to automate and scale those practices.