The Role of Data Governance in Risk Management

Keeping track of sensitive data across your organization can feel like a huge effort. Microsoft Purview is a great tool to prepare for eventual data breaches. Notice I said eventual, not potential. It’s going to happen at some point and our work can be a key part of incident detection and response. It helps you find, label, and protect important information without needing to dig through every file yourself.  I was watching the video below about Microsoft Data Security Investigations which is 100% based on data classifications which typically fall under data governance programs. I think too many times we forget how our work makes other teams’ work more effective. I’ve written about data classification in DevOps, too.

Microsoft Purview Data Classification

One of the important features of Purview is data classification. Purview automatically scans your data and first classifies your data, giving it a context and meaning like National ID Number, credit card numbers or diagnostic reports. It can even detect confidential business plans and messages. These tags help you understand what data you have and where it lives. Remember, you can’t protect data you don’t know exists.

Purview also supports machine learning-based trainable classifiers, which can recognize classes based on how they’re used in your organization, even if they don’t follow a standard format. 

But classification alone isn’t enough. That’s where data governance comes in. With Purview, you can set rules for how data should be handled such as who can access it, where it can be shared, and what happens if someone tries to move it somewhere risky. These rules help you stay compliant and mitigate data leaks.  You can even use classification to apply sensitivity labels, which I will cover and a future post.

Microsoft Purview Security Investigations

The Microsoft Purview Security feature leverages those classifications and builds upon them.  One such feature is the Data Security Investigations (DSI) tool. It is designed to help security teams understand and triage data risks, especially where sensitive information is involved.  Once data is classified, DSI uses generative AI and semantic search to analyze large volumes of content and uncover dark data. It can group data by sensitivity, subject matter, or risk level, and even detect compromised credentials or signs of insider threats. This allows analysts to investigate incidents, trace the flow of sensitive data, and collaborate across teams to contain and remediate issues. It even understands languages other than English.  These features are combined with Copilot so security teams can ask questions and get more insights.

Purview DSI video

Introducing Microsoft Purview Data Security Investigations

How Data Governance is Important for Risk Management

Data governance professionals play a critical role in the success of Microsoft Purview’s data classification and security efforts. We’re the ones who define what “sensitive” means for our organization, whether it’s customer data, financial records, or proprietary cost and price techniques and configure the classification rules accordingly. Our understanding of business context, regulatory requirements, and data flows ensures that classification policies are accurate, meaningful, and aligned with real-world risks. Without our input, automated tools like Purview wouldn’t know what to look for or how to prioritize it.  Plus, this process definitely must incorporate Human in the Loop (HITL) tasks to trust the classifications.  We bridge the gap between technology and business, making sure data protection is smart and strategic.

DSI helps us understand who’s accessing data, where it’s going, and whether anything looks suspicious. If something’s off, we can dig in and take action fast.

In short, Microsoft Purview helps you:

• Discover and document what sensitive data you have
• Manage controls for access and data filtration with automated rules
• Investigate and respond to risks quickly

Calls to Action

Here are three suggested next steps for data governance professionals working with:

1. Define and Refine Your Classification Policies: Work closely with business units and compliance teams to find what data matters most, then set up and continuously refine classification rules to show evolving risks and regulations.
2. Collaborate with Security Teams on Investigations: Partner with your security counterparts to make sure that classification are being used effectively during monitoring and investigations. Your knowledge of data context can help prioritize incidents and lead to faster, smarter responses.
3. Promote a Data-Aware Culture: Lead training and awareness efforts to help employees understand how data is classified, why it matters, and how to handle it responsibly. We can’t do all this on our own, so it pays to work with other teams to protect data.