I still see a lot of confusion about the functionality of Microsoft Purview ever since multiple products were combined into it, so I wanted to write this blog to help clear up that confusion.
Microsoft Purview is a comprehensive solution for managing, protecting, and governing data across an organization. But it’s important to understand that “Purview” is actually an umbrella brand that includes three main areas of functionality:
- Data Governance (Azure Purview) – focuses on discovering, classifying, and managing data across on-premises, multi-cloud, and SaaS environments.
- Data Security (M365 Purview) – covers data loss prevention, insider risk management, information protection, and adaptive protection. This set of capabilities evolved from what was previously known as Microsoft Information Protection (MIP).
- Data Compliance (M365 Purview) – focuses on compliance manager, eDiscovery and audit, communication compliance, data lifecycle management, and records management. These capabilities came from what was formerly called Microsoft Information Governance.
This blog will focus only on the first area—data governance—often referred to as Azure Purview. It’s the part of Microsoft Purview that gives organizations visibility into their data landscape: where data lives, how it’s used, who owns it, and whether it can be trusted.
Data governance is the foundation for any data-driven organization. It ensures that everyone—from analysts to executives—can discover and use reliable, secure, and well-understood data. Below are the six major business benefits of Microsoft’s data governance capabilities in Azure Purview.
1. Centralized Data Catalog and Discovery
(Preventing “Reinventing the Wheel”)
Imagine if every department in your organization could see, at a glance, what data already exists and what it means. That’s exactly what Azure Purview’s data catalog enables.
A data catalog is like an intelligent inventory of all your data assets—databases, reports, files, dashboards, and even SaaS data sources. Azure Purview automatically scans your environments and builds a central catalog containing metadata (the “data about the data”) such as file names, owners, schemas, and data types.
This catalog serves as a single source of truth across the enterprise. Users can search for data using familiar business terms, browse datasets, and immediately see what’s available instead of starting from scratch. For example, instead of recreating a customer sales dataset, an analyst can search “sales revenue” and find the certified, approved dataset that already exists.
Each data asset in the catalog also includes data lineage—a visual representation of where data originates, how it moves through systems, and how it’s transformed along the way. If a report shows unexpected numbers, you can trace them back through every step to the original source system.
Beyond visibility, the catalog encourages collaboration and reuse. Data stewards can add notes, business definitions, and quality tags, making it easier for others to understand and trust the data. Certified datasets can be flagged so users know they’re safe and accurate to use.
The result: no more duplicated work or disconnected knowledge. Teams can focus on insights instead of spending hours searching for or recreating data.
2. Sensitive Data Identification and Classification
(Improving Security and Building Trust)
Every organization holds sensitive data—personal details, financial records, health information—and managing that data responsibly is critical for both compliance and reputation. Azure Purview helps by automatically discovering and classifying sensitive data across your entire environment.
As Purview scans your data estate, it uses AI-powered rules and predefined patterns to detect sensitive information such as credit card numbers, Social Security numbers, or email addresses. Once detected, it applies classification labels—metadata tags that categorize data (see Classifications and sensitivity labels in Microsoft Purview).
This automatic classification provides visibility into where sensitive data resides and how it’s used. You can quickly identify which databases or files contain personal data and assess whether they’re being stored or shared appropriately.
From a business perspective, this capability is essential for compliance with regulations such as GDPR, HIPAA, and CCPA. You can demonstrate that your organization knows where its sensitive data is, who owns it, and what safeguards are in place.
And while data governance (Azure Purview) focuses on identifying and cataloging sensitive information, data security (M365 Purview) takes it a step further—enforcing rules to prevent data loss, manage insider risk, and apply encryption policies. Together, these two sides of Purview ensure that data is both understood and protected.
It’s important to note that while Azure Purview can identify and classify sensitive data, it doesn’t actually secure that data—it focuses on metadata, not the content itself. To protect the underlying information, you would use M365 Purview for items like Word documents or coordinate with, for example, an Oracle DBA to secure an Oracle database.
In short, Azure Purview strengthens trust in your data by making the invisible visible. You can’t protect what you don’t know you have—and with Purview, you finally do.
3. Governed, Self-Service Data Access
(Centralized and Compliant Access to Data)
Even with well-cataloged data, employees often face a major roadblock: getting access. Azure Purview streamlines this challenge with governed self-service access.
When a user discovers a dataset in the catalog, they can request access directly through the Purview portal. This request is automatically routed to the dataset’s owner or steward, who can approve or deny it with one click. The entire process is logged for transparency and compliance.
This approach replaces the inefficient back-and-forth of emails or IT tickets with a centralized, automated workflow. Users get faster access to the data they need for insights, while data owners maintain control and oversight.
Note that Azure Purview can only automatically grant read access in limited cases—currently, primarily for certain Azure data sources such as Azure SQL Database. For most other systems, a data administrator or DBA must manually grant access outside of Purview (for example, within Oracle or SAP), and then return to Purview to mark the request as approved.
Governed access ensures that sensitive data is shared responsibly. Access requests can be tied to specific policies—for example, only Finance department members can access financial results. Purview enforces these rules automatically, maintaining compliance without slowing productivity.
In many organizations, this becomes a cultural shift: teams start to share more data because they can do so safely and traceably. The catalog becomes not just a repository, but a trusted marketplace for data assets, where users can browse, request, and use data confidently.
The business benefit is twofold: decision-making speeds up, and risk goes down. People can access what they need, when they need it, without bypassing governance controls.
4. Data Quality and Health Monitoring
(Ensuring Reliable, Actionable, and Governed Data)
High-quality data is the foundation of trustworthy analytics and sound decision-making. Azure Purview now includes powerful data quality and health monitoring capabilities that help organizations continuously measure, improve, and govern the quality of their data.
Data Quality
With Purview’s new data quality model, organizations can identify and fix data quality issues using a no-code/low-code approach. Business users, data stewards, or domain owners can define rules at different levels—business domains, data products, or individual data assets—without writing complex code.
Purview also provides a growing library of out-of-the-box (OOB) rules that check for common problems such as duplicate rows, empty fields, and missing or non-unique values. Copilot can even suggest new rules automatically, helping teams establish data standards faster.
Once rules are configured, the data quality model evaluates your data against those rules and generates data quality scores at the asset, product, or domain level. These scores give you a quick snapshot of how your data measures up to the business rules you’ve defined.
Data profiling and data quality scans further enhance visibility:
- Data profiling provides quick insights from a small sample set to spot potential issues early.
- Data quality scans perform in-depth analysis across full data sets to detect inconsistencies and anomalies.
When problems are detected—such as a sudden drop in a quality score or unusual data patterns—Purview can generate data quality actions that highlight what needs attention. These actions can be assigned to specific people to resolve issues using tools like Azure Data Factory. Once the fix is complete, the issue can be marked as resolved, maintaining a full audit trail.
You can also configure data quality alerts that notify users when certain conditions are met—for example, when the data quality score for the Sales domain drops below 50%. Alerts appear within Purview and can also be sent by email, ensuring that data stewards can take quick corrective action.
Finally, Purview allows you to define data access policies at the business domain, data product, or glossary-term level. Any time a glossary term is applied to a data product, all its associated policies—such as access limits, required approvals, or permissions for data copies—are automatically enforced. This unifies governance and quality under one framework.
Health Controls
Purview’s health controls track your organization’s overall progress toward complete data governance. These controls measure how well your data environment aligns with governance standards and provide a governance health score.
Examples of health controls include:
- Metadata completeness – Are key fields documented?
- Cataloging – Are all major data sources registered?
- Classification – What percentage of assets are classified?
- Access entitlement – Who can access what data, and is it governed?
- Data quality – How does the data score against your rules?
Data officers can configure thresholds that define red, yellow, or green indicators for each metric. For instance, you might set a target that 80% of data assets must be classified or that 90% should be mapped to data products for discoverability.
Health Actions
Whenever Purview detects gaps or misalignments—such as unclassified assets or unmapped data products—it automatically creates health actions. These actions appear in a new Action Center that aggregates governance-related tasks by role, data product, or business domain.
Each action includes recommendations for how to fix the issue and can be assigned to an owner for resolution. Clicking an action provides direct guidance on how to bring the data asset or domain back into compliance. As teams complete these actions, the organization’s overall governance posture improves.
This approach turns governance into an interactive, team-based process. Instead of static reports, Purview provides a living dashboard of your data’s health—showing where to focus next and tracking progress over time. By cleaning up outstanding actions and maintaining high-quality data, your organization strengthens both trust and agility in its data-driven decision-making.
Note that data quality and health monitoring were one of the new features added last year (see Microsoft Purview new data governance features).
5. Business Glossary
(Speaking a Common Data Language)
Many data problems start not with numbers, but with words. Departments often use different terms for the same concept, leading to confusion and misaligned reporting.
Azure Purview solves this with a Business Glossary—a central library of business terms and definitions. This glossary creates a shared vocabulary that connects business language to technical data assets.
For instance, the term “Active Customer” might be defined as “a customer with at least one purchase in the last 12 months.” That definition is stored in Purview and linked to the specific datasets and reports that use it. Everyone—from Finance to Marketing—can see and use the same definition.
This not only ensures consistent understanding but also prevents data disputes. When executives review dashboards or metrics, they know that terms like “Revenue” or “Churn Rate” mean the same thing across the organization.
Glossary terms can also be linked to governance policies. For example, a glossary term like “Personal Data” can automatically trigger stricter access controls or encryption requirements whenever it’s applied to a dataset.
The result: clearer communication, fewer misunderstandings, and stronger alignment between business and IT.
6. Business Domains and Data Products
(Organizing Data for Business Context and Discoverability)
A major advancement in Azure Purview’s data governance framework is the introduction of business domains and data products—two concepts that bring structure, business meaning, and reusability to your data catalog. These features help organizations align their data estate with how the business actually operates.
Business Domains
A business domain is a framework for organizing data around a common business purpose or capability, such as Sales, Finance, or Marketing. Think of it as a mini catalog inside your main data catalog—a logical boundary that aligns your data assets with your organizational structure.
Business domains make it easier to manage business concepts, assign ownership, and define governance rules. They differ from the technical domains used in the Data Map (known as collections), which group assets by project, technology, or ownership. However, business domains can be mapped to these collections, so assets tied to a business domain are automatically linked to the corresponding technical assets beneath it.
Within each business domain, you can:
- Create and manage business domains to organize and curate your catalog.
- Assign owners and stewards responsible for data governance within that domain.
- Relate business domains to the underlying data collections in the Data Map.
- Create glossary terms for key business concepts—using Copilot to suggest relevant terms automatically.
- Monitor the health of your domains, taking timely actions to keep them well-governed.
- Define business objectives and key results (OKRs)—such as increasing sales by 10% or reducing support cases by 3%—and track progress directly within Purview.
- Define critical data elements (CDEs), which logically group key pieces of information (for example, mapping “CustID” in one table and “CID” in another under a single “Customer ID” concept).
Business domains provide a way to connect the technical world of data assets with the business world of strategy and operations. By aligning data governance structures with business functions, organizations can make data more understandable, more accessible, and more relevant.
Data Products
A data product represents a curated group of data assets packaged together for a specific business use case or purpose. Data products are assigned to business domains and act as logical business concepts that make data easier to find and use.
Instead of users hunting across dozens of individual tables or files, a data product bundles them all into one logical unit. For example, a “Global Sales Revenue for 2023CY” data product could include tables, files, and Power BI reports related to sales performance. When users request access to that data product, they automatically get access (after approval) to all the associated assets—no more requesting permissions for 15 separate tables.
Data products streamline governance and improve efficiency:
- Organization: Each data product belongs to one business domain but can be discovered across multiple domains.
- Discoverability: Data products are searchable using natural language. For instance, you can type, “Show me daily retail sales data for the past six months,” and Purview will surface relevant products.
- Context: Descriptions within data products include use cases, examples, and instructions for analysis.
- Ownership: Each data product has an owner—often a data scientist, analyst, or steward—responsible for maintaining its accuracy and usefulness.
- Governance: Access requests, approvals, and policies apply at the data product level, ensuring consistency and compliance.
Data products also tie back to glossary terms and governance policies. For instance, if a glossary term labeled “Customer Data” includes specific access policies, applying that term to a data product automatically enforces those policies.
The hierarchy in Azure Purview now looks like this:
Business Domains → Data Products → Data Assets.
An example might be:
Sales (Business Domain) → Global Sales Revenue for 2023CY (Data Product) → Global Sales for 2023 Power BI Report (Data Asset).
This model gives users a clean, intuitive way to explore data. Instead of sifting through thousands of assets, they can browse or search by business domain, open a data product, and find everything they need in one place. On the Data Product Search page, users can explore data products, view their details, and track data access requests using the “My Data Access” tab—all from a single, business-centric interface.
Why Business Domains and Data Products Matter
Together, business domains and data products transform Azure Purview from a technical catalog into a business-aligned data marketplace.
- Business domains give your data structure and purpose.
- Data products make it consumable and actionable.
This approach empowers teams to focus on business outcomes—like growing revenue or improving customer satisfaction—while ensuring the data behind those goals is well-organized, governed, and easy to find.
It’s the next step in making data governance not just a compliance exercise, but a true business enabler.
Note that business domains and data products were one of the new features added last year (see Microsoft Purview new data governance features).
Conclusion
Microsoft Purview is far more than a simple data catalog—it’s a unified ecosystem for governing, securing, and understanding data across your entire organization. While M365 Purview focuses on data security (protecting sensitive information and preventing data loss) and data compliance (managing records, retention, and regulatory requirements), Azure Purview is all about data governance—helping you discover, understand, organize, and trust your data.
The data catalog prevents duplication and drives data discovery.
The classification engine identifies sensitive data, improving transparency and compliance readiness.
The governed access framework streamlines how users request and receive permission to use data while maintaining control.
The new data quality and health monitoring capabilities ensure that your data is accurate, complete, and reliable—empowering your teams to make decisions with confidence.
The business glossary aligns everyone around a consistent vocabulary, breaking down communication barriers between business and technical teams.
And the introduction of business domains and data products brings everything together—organizing data into meaningful business contexts and packaging it into reusable, governed assets that anyone in the organization can find and use.
Together, these components create a living, breathing governance framework that turns data chaos into clarity. Azure Purview provides not just visibility into your data, but also accountability, structure, and business meaning—all built on a foundation of automation and AI assistance.
In short:
- Azure Purview helps you govern and understand your data.
- M365 Purview helps you protect and comply with your data.
By combining these two sides of Purview, organizations can finally achieve what most only talk about: a complete, end-to-end data governance and protection strategy—one that’s modern, scalable, and aligned to how the business actually operates.
The post Microsoft Purview: The Key Benefits of Data Governance first appeared on James Serra's Blog.