Azure Purview Basics: Managing Data Governance Seamlessly – IT Exams Training

In the digital era, data has emerged as one of the most valuable assets for businesses across all industries. Organizations collect and generate enormous volumes of data every day—from customer information and transaction records to operational metrics and social media interactions. This data, when properly managed and analyzed, has the power to drive innovation, improve decision-making, and create a competitive advantage.

However, the rapid growth of data also brings significant challenges and risks. Many organizations are unaware of the exact nature of their data assets, including where data resides, who has access to it, and how it flows across different systems. Without clear visibility and control, businesses expose themselves to operational inefficiencies, regulatory non-compliance, data breaches, and reputational damage.

The introduction of stringent data protection regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) has further underscored the need for effective data governance. These regulations require organizations to maintain transparency, ensure data accuracy, and uphold individuals’ rights regarding their data. Failing to comply can result in hefty fines and legal consequences.

As a result, organizations are recognizing that data governance is not just an IT concern but a strategic imperative. They need systems and processes that can provide a unified, comprehensive view of their data assets, enforce security and privacy policies, and facilitate responsible data usage throughout the organization.

What is Data Governance?

At its core, data governance refers to the set of policies, roles, standards, and processes that ensure data is managed properly and used responsibly. According to recognized industry definitions, data governance involves specifying decision rights and establishing accountability frameworks to assure acceptable behavior in the valuation, generation, consumption, and management of data and analytics.

Data governance encompasses multiple dimensions, including:

Data quality: Ensuring data is accurate, complete, and consistent so that it can be trusted for analysis and operational use.
Data security and privacy: Protecting data from unauthorized access and ensuring compliance with legal requirements.
Data availability: Making sure that the right data is accessible to authorized users when needed.
Data lifecycle management: Defining how data is created, maintained, archived, and disposed of.
Metadata management: Capturing and managing information that describes data assets, their meaning, lineage, and relationships.
Policy enforcement: Implementing rules and controls that govern data use, sharing, and protection.

A robust data governance program helps organizations to break down silos, improve data consistency, and reduce operational risks. It provides a foundation for trusted analytics and business intelligence by enabling users to find, understand, and rely on the data they consume.

Challenges Organizations Face Without Proper Data Governance

Without effective data governance, organizations struggle with numerous challenges that hinder their ability to leverage data strategically:

Data Silos: Data is often fragmented across multiple systems, departments, and formats, making it difficult to get a holistic view.
Poor Data Quality: Inconsistent, incomplete, or inaccurate data can lead to faulty analysis and poor business decisions.
Security Risks: Sensitive data may be exposed to unauthorized users, increasing the risk of data breaches and compliance violations.
Lack of Data Visibility: Without knowing where data resides or how it flows, organizations cannot effectively manage or protect it.
Compliance Failures: Inability to meet regulatory requirements regarding data handling, retention, and privacy can result in legal penalties.
Operational Inefficiencies: Redundant data and manual efforts to locate and manage information increase costs and delay initiatives.
Decision-Making Delays: If users cannot easily find trusted data, it slows down reporting, analytics, and innovation.

These issues highlight the critical need for technology solutions that support automated data discovery, classification, and governance at scale.

The Role of Technology in Enabling Data Governance

Implementing a successful data governance strategy requires more than policies and procedures—it demands the right technology platform. Organizations need a unified solution that can:

Automatically discover and catalog data assets across on-premises and cloud environments.
Classify data based on sensitivity and business context to apply appropriate controls.
Track data lineage to provide transparency into data flow and transformations.
Provide a centralized interface for data stewards and business users to manage and explore data.
Deliver analytics and insights to monitor governance effectiveness and compliance.
Integrate with security and data protection frameworks to enforce policies seamlessly.

Such a platform reduces manual effort, increases accuracy, and provides ongoing visibility and control. It enables organizations to manage data as a strategic asset rather than an unmanaged liability.

Introducing Azure Purview as a Unified Data Governance Solution

Azure Purview is a cloud-native data governance solution designed to meet the needs of modern organizations managing complex, distributed data estates. It provides a unified platform that helps organizations discover, classify, and govern their data across on-premises systems, multiple clouds, and SaaS applications.

Azure Purview automates the process of metadata collection and classification using advanced scanning and built-in classifiers. It creates a comprehensive data map that provides up-to-date insights into data location, lineage, and sensitivity. This metadata repository serves as the foundation for a searchable data catalog and governance workflows.

Key capabilities of Azure Purview include:

Automated Data Discovery: Scan diverse data sources to identify and catalog data assets without manual intervention.
Sensitive Data Classification: Detect and label sensitive information such as personal data, financial records, or intellectual property.
End-to-End Data Lineage: Visualize the flow of data across systems and transformations to understand its journey and impact.
Data Catalog: Provide business users and analysts with a semantic search tool to find trusted data quickly.
Data Insights: Offer dashboards for data officers and administrators to monitor governance status and risks.
Integration with Security Frameworks: Use Microsoft Information Protection sensitivity labels to enforce access controls and data protection.

Azure Purview is built on open standards and integrates with existing Microsoft services and third-party tools, making it adaptable to varied environments. Its pay-as-you-go pricing model allows organizations to adopt governance incrementally without heavy upfront investments.

Why Organizations Are Adopting Azure Purview

The demand for a unified data governance solution like Azure Purview is growing because it addresses critical challenges faced by modern enterprises:

It reduces the complexity of managing data across hybrid and multi-cloud environments.
It enables compliance with evolving data privacy and security regulations.
It improves data quality and consistency by providing centralized governance.
It empowers users with self-service access to trusted data, enhancing productivity.
It lowers operational costs by automating metadata management and reducing manual processes.
It provides executives and data officers with actionable insights into data usage and risk.

By adopting Azure Purview, organizations can transform their data governance from a fragmented, manual effort into a scalable, automated discipline that supports business goals and regulatory compliance.

The Foundation for Effective Data Governance

Data governance is an essential capability for organizations seeking to harness the full value of their data assets while managing risk and meeting regulatory demands. The complexity of today’s data environments demands modern governance solutions that can provide automated discovery, classification, and lineage tracking across diverse data sources.

Azure Purview offers a unified platform tailored to these needs, enabling organizations to create a comprehensive, real-time map of their data estate. This foundation supports trusted data discovery, effective policy enforcement, and continuous governance monitoring.

As businesses continue to recognize data as a strategic asset, implementing a solution like Azure Purview becomes critical to achieving data transparency, security, and usability at scale.

Core Components of Azure Purview

Azure Purview is composed of several key components that work together to deliver a comprehensive data governance solution. Understanding these components is crucial to appreciating how Purview supports data management across an organization’s data estate.

Purview Data Map

The Data Map is the foundational element of Azure Purview. It serves as a cloud-native platform-as-a-service (PaaS) that continuously collects and maintains metadata from all registered data sources. This metadata includes technical details about the data’s structure, location, usage, and sensitivity.

Data Map’s core functionality includes:

Automated Scanning and Metadata Extraction: Purview uses built-in scanners to automatically connect to on-premises and cloud data sources. These scanners harvest metadata at regular intervals, ensuring the Data Map stays current.
Classification and Labeling: Using machine learning-based classifiers, the Data Map detects sensitive data types such as personally identifiable information (PII) or financial records and applies relevant labels.
Metadata Storage and Management: The Data Map stores all metadata in a scalable repository that is accessible via APIs and user interfaces, supporting diverse governance workflows.

By building this up-to-date metadata repository, the Data Map enables organizations to gain a comprehensive understanding of their data assets without manual inventory or tagging.

Purview Data Catalog

Built on top of the Data Map, the Data Catalog offers a rich, user-friendly experience for business users, data analysts, and data scientists to discover, understand, and trust data.

Key features of the Data Catalog include:

Semantic Search: Users can search for data using business terms, technical metadata, or operational context. This semantic layer makes it easier to find relevant data assets quickly.
Metadata Enrichment: The catalog provides detailed metadata about each data asset, including definitions, classifications, owners, and lineage information.
Trusted Source Validation: Users can verify the origin and quality of data, helping them to make informed decisions based on reliable data.
Collaborative Features: Business glossary terms and annotations can be shared and maintained collaboratively, fostering data literacy and shared understanding.

The Data Catalog transforms complex technical metadata into actionable business knowledge, empowering users to leverage data confidently.

Purview Data Lineage

Understanding how data flows through systems is critical for impact analysis, compliance, and troubleshooting. Azure Purview offers end-to-end data lineage tracking that provides clear visibility into the data’s journey from source to destination.

Features of Data Lineage include:

Visual Lineage Graphs: Interactive visualizations show the transformation and movement of data through pipelines, databases, and reports.
Cross-System Tracking: Lineage spans multiple platforms, including cloud services, on-premises databases, and analytics tools.
Integration with Data Factory and Power BI: Purview automatically ingests lineage from Azure Data Factory pipelines and Power BI datasets, reducing manual effort.
Impact Analysis: Users can assess how changes in data sources might affect downstream reports or applications, enabling risk mitigation.

This comprehensive lineage visibility is vital for maintaining data quality, ensuring compliance, and troubleshooting data issues efficiently.

Purview Data Insights

Data officers, compliance managers, and security teams need dashboards and reports to monitor governance health and data risk across the enterprise. Purview Data Insights provides these capabilities through analytics and visualization.

Key aspects include:

Data Scanning Overview: Visual summaries show which data sources have been scanned, how frequently, and the volume of data classified.
Sensitive Data Tracking: Insights reveal where sensitive data resides and how it is accessed, highlighting potential compliance risks.
Usage and Access Analytics: Reports provide understanding of who is consuming data and how it flows within the organization.
Governance Metrics: KPIs such as data coverage, classification rates, and policy adherence can be monitored in real time.

By providing actionable insights, Purview Data Insights helps stakeholders identify gaps, prioritize governance efforts, and demonstrate compliance.

How Azure Purview Supports a Hybrid and Multi-Cloud Environment

Modern organizations often operate data environments that span on-premises systems, multiple cloud providers, and SaaS platforms. Managing governance across this hybrid, multi-cloud landscape is complex, yet critical.

Azure Purview addresses this challenge by:

Supporting Diverse Data Sources: Purview currently supports a broad range of data sources, including SQL Server, Azure Data Lake Storage (Gen1 and Gen2), Azure Blob Storage, Azure Synapse Analytics, Power BI, SAP, Oracle, Teradata, and more.
Hybrid Scanning Capability: Purview can scan on-premises data through self-hosted integration runtimes that securely connect to local sources without moving data off-site.
Cross-Cloud Metadata Aggregation: Metadata from multiple clouds and on-premises sources is unified in the Purview Data Map, providing a single pane of glass for governance.
Cloud-Native Architecture: Being a cloud service itself, Purview benefits from scalability, continuous updates, and integration with other Azure security and identity services.

This unified approach ensures consistent governance policies and visibility, regardless of where the data resides.

Data Classification and Sensitive Data Discovery

One of the most critical aspects of data governance is identifying sensitive data and applying appropriate protection measures. Azure Purview offers automated classification capabilities designed to address this need efficiently.

Automated Classification

Purview comes with a rich library of built-in classifiers that use pattern matching, machine learning, and rule-based logic to detect sensitive data, such as:

Personally identifiable information (PII)
Payment card information (PCI)
Health records (HIPAA)
Financial information
Intellectual property

Classifiers scan data at rest across registered sources and apply sensitivity labels based on Microsoft Information Protection standards.

Custom Classifiers

Organizations can extend Purview’s classification by creating custom classifiers tailored to their specific data types and compliance requirements. This flexibility ensures that unique or industry-specific data is appropriately handled.

Sensitivity Labels

Once data is classified, Purview applies sensitivity labels that integrate with Microsoft’s broader data protection ecosystem. These labels help enforce access controls, encryption, and data loss prevention policies across platforms such as Microsoft 365.

Metadata Management and Business Glossary

Metadata is the backbone of data governance. Azure Purview excels in capturing and managing metadata that describes data assets comprehensively.

Types of Metadata Managed

Technical Metadata: Details about data structures, formats, and physical locations.
Business Metadata: Definitions, descriptions, and context provided by business users.
Operational Metadata: Information about data usage, refresh cycles, and quality metrics.
Lineage Metadata: Relationships and transformations showing data flow.

Business Glossary

Purview includes a collaborative business glossary where organizations can define and maintain standard business terms and definitions. This glossary:

Ensures consistent language across the enterprise
Facilitates semantic search by mapping terms to data assets
Supports automated tagging and classification
Enhances data literacy and cross-team communication

A well-maintained business glossary is essential for bridging the gap between technical data and business understanding.

Security and Compliance Integration

Azure Purview supports data governance not only by cataloging and classifying data but also by integrating with security frameworks to enforce policies and maintain compliance.

Microsoft Information Protection Integration

Sensitivity labels applied through Purview are part of Microsoft Information Protection, allowing consistent enforcement of security policies across Microsoft services. This integration:

Controls access to sensitive data based on user roles and conditions
Enables encryption and data masking where required
Supports auditing and reporting for compliance purposes

Data Residency and Privacy

Purview respects data residency requirements by ensuring that metadata and classification processes do not transfer or store sensitive data outside the region where the service is deployed. This consideration is crucial for compliance with regional data protection laws.

In this section, we explored the core components of Azure Purview and how they work together to deliver a powerful data governance platform. From the foundational Data Map to the user-friendly Data Catalog and comprehensive Data Lineage, Purview equips organizations with the tools needed to discover, classify, and understand their data assets.

We also discussed Purview’s ability to operate seamlessly in hybrid and multi-cloud environments, its automated sensitive data classification capabilities, and the critical role of metadata management and business glossaries in driving data literacy and consistency.

Finally, we examined how Purview integrates with security frameworks to enforce data protection and compliance policies, helping organizations safeguard their data while meeting regulatory requirements.

Practical Use Cases of Azure Purview

Azure Purview’s unified data governance capabilities address several real-world business challenges. Understanding these use cases can help organizations realize their value and tailor deployments effectively.

Regulatory Compliance and Risk Management

Organizations face increasing pressure to comply with regulations such as GDPR, CCPA, HIPAA, and others that mandate strict controls over personal and sensitive data.

Azure Purview helps by:

Automatically Discovering Sensitive Data: Classifiers scan data repositories to identify sensitive information and flag potential compliance risks.
Maintaining Data Lineage and Audit Trails: End-to-end lineage tracking supports investigations and audits by clearly showing where data originated, how it was transformed, and who accessed it.
Enforcing Policies via Sensitivity Labels: Labels enforce access restrictions and data handling rules across platforms, reducing the risk of unauthorized disclosure.
Providing Insights for Compliance Reporting: Data Insights dashboards give compliance officers visibility into data governance posture, enabling proactive risk mitigation.

This reduces manual compliance efforts and helps avoid costly fines or reputational damage.

Accelerating Data Discovery and Self-Service Analytics

Data consumers such as business analysts, data scientists, and engineers often struggle to locate and understand relevant data assets, slowing down analytics projects.

Azure Purview enhances productivity by:

Offering a Semantic Search Experience: Users can find data assets using business terms without needing deep technical knowledge.
Providing Rich Metadata and Glossary Context: Metadata and glossary terms help users understand data meaning, quality, and provenance.
Enabling Trusted Data Access: By knowing data classification and lineage, users can confidently use data while respecting compliance rules.
Supporting Collaboration: Teams can annotate assets and share knowledge, fostering a data-driven culture.

Self-service analytics becomes more feasible and faster, accelerating business insights.

Data Lifecycle and Quality Management

Ensuring data quality and proper lifecycle management is essential for trustworthy analytics and operational efficiency.

Azure Purview supports this by:

Providing Data Profiling and Quality Metrics: Profiling helps identify data inconsistencies, missing values, or duplicates.
Enabling Data Ownership and Stewardship: Assigning data owners and stewards ensures accountability for data quality and lifecycle policies.
Automating Data Catalog Updates: Scheduled scans keep metadata and classifications up-to-date, reflecting data changes over time.
Facilitating Data Retention and Archival Policies: Insights into data usage and classification aid decisions on data retention and secure disposal.

Effective lifecycle management reduces storage costs and improves data reliability.

Benefits of Implementing Azure Purview

Adopting Azure Purview delivers numerous advantages beyond compliance, impacting operational efficiency and business value.

Enhanced Data Visibility and Trust

Purview provides a centralized, comprehensive view of data assets, enabling organizations to:

Know what data exists and where it resides
Understand data sensitivity and usage patterns.
Establish trust in data quality and lineage

This visibility is foundational for confident data-driven decision-making.

Cost Savings and Operational Efficiency

Automated metadata management and data classification reduce manual effort in:

Data inventory and discovery
Compliance audits and reporting
Data quality monitoring and issue resolution

These efficiencies translate into lower operational costs and faster time to value.

Improved Collaboration and Data Literacy

Purview’s business glossary and collaborative catalog features foster a shared understanding of data across business and technical teams. This enhances:

Data literacy and self-service analytics
Cross-departmental cooperation
Faster onboarding of new data users

Such collaboration drives a data culture aligned with business objectives.

Scalability and Integration

As a cloud-native service, Azure Purview scales with organizational growth and evolving data landscapes. Its integration with the Azure ecosystem tools and APIs enables:

Seamless onboarding of new data sources
Extension of governance workflows via automation
Consistent governance across hybrid and multi-cloud environments

This future-proofs data governance initiatives.

Challenges and Limitations of Azure Purview

While Azure Purview offers significant promise, it is important to be aware of current challenges and limitations when planning adoption.

Limited Data Source Coverage

Though support is growing, Purview currently lacks connectors for many popular and legacy systems, requiring:

Manual metadata ingestion or custom connectors
Potential gaps in governance coverage

This may necessitate phased rollouts or hybrid approaches.

User Interface and Feature Gaps

Some users report limitations such as:

Inability to delete or modify categorized assets via the UI
Lack of automation for alerts or policy enforcement
No support for categorizing compressed files like ZIP archives
Absence of a built-in Data Marketplace for asset sharing

These gaps may affect user experience and governance maturity.

Storage and Capacity Constraints

Current capacity limits (such as 10GB for small capacity units) may constrain large-scale deployments, requiring careful planning and monitoring of:

Metadata volume growth
Storage usage patterns

Organizations should evaluate these limits against data estate size.

Early Stage Maturity

As a relatively new service, Azure Purview is evolving rapidly. Organizations should:

Monitor product updates and roadmap closely
Maintain flexibility in governance strategies.
Engage with support and community for best practices

Despite current limitations, ongoing improvements indicate a promising future.

Adoption Considerations and Best Practices

To maximize the value of Azure Purview, organizations should follow thoughtful adoption strategies.

Define Clear Governance Objectives

Establish specific goals such as:

Compliance with regulations
Improved data discovery and analytics
Enhanced data quality and stewardship

Clear objectives help focus Purview deployment and measure success.

Engage Stakeholders Across the Organization

Successful governance requires collaboration among:

Data owners and stewards
IT and security teams
Business users and analysts

Engagement ensures shared ownership and smoother change management.

Start Small and Scale Gradually

Begin with a pilot program targeting critical data domains or high-risk areas. This approach enables:

Learning and refining governance processes
Demonstrating quick wins and ROI
Building organizational buy-in

Gradual scaling reduces risks and maximizes adoption.

Invest in Training and Change Management

Equip users with training on:

Data governance concepts and benefits
Purview features and workflows
Best practices for data stewardship and collaboration

Change management fosters a data-driven culture and sustainable governance.

Monitor and Evolve Governance Over Time

Governance is an ongoing journey. Use Purview’s insights and metrics to:

Track progress against objectives
Identify gaps or emerging risks.
Adjust policies and processes accordingly.

Continuous improvement keeps governance aligned with business needs.

This series covered practical use cases where Azure Purview helps organizations manage compliance, accelerate data discovery, and improve data quality. We explored the benefits of improved visibility, operational efficiency, collaboration, and scalability delivered by Purview.

We also addressed current challenges, including limited data source support, UI gaps, capacity constraints, and the early maturity stage of the product. Finally, adoption of best practices emphasizes clear objectives, stakeholder engagement, phased deployment, training, and continuous monitoring to ensure successful governance outcomes.

Advanced Capabilities of Azure Purview

As organizations mature in their data governance journey, advanced features in Azure Purview help meet complex needs beyond basic data discovery and classification.

Data Lineage and Impact Analysis

Understanding how data moves and transforms through various systems is critical for troubleshooting, compliance, and impact assessment.

Azure Purview provides:

End-to-End Data Lineage Visualization: Interactive maps trace data from source to destination, revealing transformations, aggregations, and data flow across pipelines.
Impact Analysis: By understanding lineage, organizations can assess the potential effects of changes in data sources on downstream analytics and reports.
Integration with Data Pipelines: Lineage can be automatically ingested from Azure Data Factory and other data integration services, ensuring current and accurate maps.

This capability aids in root cause analysis and reduces risk in data operations.

Sensitive Data Classification and Protection

Purview’s classification engine employs built-in and customizable classifiers to automatically tag sensitive information such as personally identifiable information (PII), financial data, and intellectual property.

Key features include:

Automated Sensitive Data Discovery: Scans across data stores to detect sensitive data patterns.
Custom Classifiers: Organizations can define tailored classifiers to address specific business needs.
Integration with Microsoft Information Protection (MIP): Sensitivity labels propagate across Microsoft 365 workloads, enforcing data protection policies consistently.
Policy Enforcement: Enables restrictions on data access and sharing based on classification.

This comprehensive approach strengthens security posture and regulatory compliance.

Data Sharing and Collaboration

Azure Purview facilitates secure data sharing within and beyond organizational boundaries.

Capabilities include:

Data Sharing Without Data Movement: Enables external partners to access data securely without duplicating datasets or requiring FTP transfers.
Governed Access Controls: Access policies ensure that only authorized users can view or manipulate data.
Collaboration via Business Glossary: Standardized definitions improve communication and data understanding among diverse teams.
Audit Trails and Monitoring: Track data sharing activities to maintain transparency and accountability.

This supports data monetization, joint ventures, and ecosystem participation securely and efficiently.

The Outlook of Azure Purview

Azure Purview is evolving rapidly, with Microsoft’s roadmap targeting enhanced functionality and broader integration.

Expected developments include:

Expanded Data Source Connectors: Inclusion of more third-party systems and big data platforms.
Enhanced Automation and Alerting: Automated workflows and real-time notifications for governance events.
Advanced Analytics and AI Integration: Leveraging AI for anomaly detection, predictive data quality, and smarter metadata management.
Improved User Experience: Simplified UI and richer management capabilities.
Deeper Integration Across Azure Services: Tighter coupling with Azure Synapse, Power BI, and security tools.

These advancements will strengthen Purview’s position as a comprehensive enterprise-grade data governance solution.

Strategic Impact of Azure Purview on Organizations

Beyond technical capabilities, adopting Azure Purview drives significant strategic benefits.

Enabling Data as a Strategic Asset

By providing transparency, control, and trust in data, organizations can shift from data chaos to data confidence. This empowers:

Data-driven innovation
Enhanced customer experiences
Operational agility
Competitive differentiation

Data becomes a manageable and monetizable asset rather than a liability.

Supporting Regulatory and Ethical Data Practices

Purview helps institutionalize responsible data management aligned with evolving legal and ethical standards. This reduces risk, builds trust with customers and regulators, and upholds corporate reputation.

Facilitating Digital Transformation

Unified data governance is foundational for digital transformation initiatives such as cloud migration, AI adoption, and advanced analytics. Azure Purview provides the governance scaffolding needed to safely unlock data value at scale.

In today’s data-driven world, effective data governance is no longer optional. Organizations must understand their data landscape comprehensively to mitigate risks and capitalize on opportunities.

Azure Purview offers a powerful, cloud-native platform to unify governance across hybrid and multi-cloud environments. Its rich features—automated data discovery, sensitive data classification, end-to-end lineage, and collaboration tools—equip businesses to govern data responsibly and efficiently.

While still maturing, Azure Purview’s trajectory is promising. With continued enhancements and thoughtful adoption, it can become the cornerstone of enterprise data governance, helping organizations turn data into a true strategic asset.

Ultimately, embracing Azure Purview supports the vision of democratizing data with trust, ensuring that data is accessible, understandable, and secure for all who need it.

Final Thoughts

Data governance is a critical enabler for organizations seeking to harness the full potential of their data assets while navigating the complex landscape of regulatory compliance and security risks. Azure Purview stands out as a modern, scalable solution that addresses many of the key challenges in managing data across diverse environments.

Its unified approach to metadata management, data classification, and lineage provides businesses with the transparency and control needed to foster trust in their data. By automating discovery and classification processes, Azure Purview reduces manual effort and helps maintain data quality and compliance at scale.

While it is still evolving, the platform’s integration with other cloud services and its roadmap for expanded capabilities make it a compelling choice for enterprises embarking on their data governance journey. Adopting Azure Purview not only helps protect sensitive information but also empowers data consumers by making data easier to find, understand, and use responsibly.

In a world where data is often described as the new currency, having a robust governance framework like Azure Purview is no longer just beneficial—it is essential. Organizations that invest in data governance today will be better positioned to innovate, comply, and compete in the data-driven economy of tomorrow.