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Data Governance

What is Data Governance?

Data governance is a comprehensive approach that comprises the principles, practices, and tools to manage an organization's data assets throughout their lifecycle. By aligning data-related requirements with business strategy, data governance provides superior data management, quality, visibility, security, and compliance capabilities across the organization. Implementing an effective data governance strategy allows companies to make data easily available for data-driven decision-making while safeguarding their data from unauthorized access and ensuring compliance with regulatory requirements.

What are the Business Benefits of Data Governance?

Data governance is essential for unlocking the value of data, which is a critical asset for organizations. By implementing a robust data governance approach, businesses can leverage their data assets, gain a competitive edge, and earn and maintain customer trust by ensuring sound data and privacy practices.

Increased Operational Efficiency and Reduced Costs

Effective data governance allows organizations to create a single source of truth for their data estate, preventing data sprawl and silos, and reducing duplication. This leads to increased efficiency, reduced costs, and easier management of security and governance concepts across the data estate.

Improved Productivity and Faster Decision-Making

Data governance promotes data democratization by ensuring data accuracy, consistency, and trustworthiness. It helps data users find high-quality data quickly, promoting a better understanding of the data's meaning and context, leading to increased productivity and faster decision-making.

Enhanced Collaboration and Value Realization

A strong data governance program lays the foundation for enhanced data collaboration and sharing across teams, business units, and partners. This helps organizations promote knowledge sharing and build a better data culture, leading to increased innovation, better decision-making, and maximizing the value of their data.

Enhanced Security and Privacy

Data governance mitigates security and privacy risks by implementing controls and processes to prevent unauthorized access and misuse of sensitive data. It promotes a culture of trust and transparency with stakeholders.

Better Compliance with Regulations and Standards

Effective data governance results in better compliance with regulatory requirements, such as HIPAA, FedRAMP, GDPR, or CCPA. This protects the organization's reputation, avoids potential financial and legal consequences, and increases stakeholder trust.

Key Elements of Data Governance

Data Cataloging

Effective data governance requires knowledge of the data that exists within an organization. This is where a data catalog comes in, as it provides a centralized metadata repository for an organization's data assets. A data catalog allows stakeholders to quickly discover, understand, and access the data they need, improving data-related activities such as discovery, governance, and analytics. Incorporating a data catalog into a governance program can help organizations improve their data management, enhance collaboration, reduce redundancy, and ensure proper access controls and audit information retrieval.

Data Quality

Ensuring high data quality is crucial for accurate analytics, informed decision-making, and cost-effectiveness. Data quality directly impacts the reliability of data-driven decisions and is a key aspect of data governance. To maintain effective data governance, organizations must prioritize the evaluation of key data quality attributes such as accuracy, completeness, freshness, and compliance with data-quality rules. Therefore, a strong focus on data quality is essential in any data governance strategy, as it helps trace data lineage, enforce data quality rules, and track changes.

Data Classification

Data classification involves organizing and categorizing data based on its sensitivity, value, and criticality. Classification allows organizations to identify and classify data based on its risk level and importance, allowing them to apply appropriate security measures and policies. A robust data classification system enhances data governance, reduces risks, and ensures data quality and protection at scale.

Data Security

Effective data access management is crucial for data security and governance, and a good data security governance program should include access controls that define which groups or individuals can access what data. These controls can be highly specific, down to the individual record or file. As data breaches and regulations such as GDPR and CCPA pose increased risks, businesses must establish clear governance policies that define who can access sensitive data sets and how to track any misuse.

Auditing Data Entitlements and Access

Effective data access auditing is a critical aspect of data governance and security governance programs, particularly in regulated industries. By understanding who has access to what data and tracking recent access, organizations can proactively identify over-entitled users or groups and adjust their access accordingly, minimizing the risk of data misuse.

Data Lineage

Data lineage captures relevant metadata and events throughout the data's lifecycle, providing an end-to-end view of how data flows across an organization's data estate. As an essential pillar of a pragmatic data governance strategy, data lineage enables organizations to become compliant and audit-ready while reducing the operational overhead of creating audit trails manually, and providing trusted sources for audit reports.

Data Discovery

Data discovery is critical to accelerate data democratization and unlock the true value of the data. Organizations should view data discovery as a fundamental aspect of their data governance strategy. It enables data teams to easily locate data assets across the organization, collaborate on various projects, and innovate quickly