Data Term Definitions

Data Governance

Data governance is the set of rules, processes, and roles that safeguard organizational data.

What Is Data Governance?

Data governance is the set of rules, processes, and roles that safeguard an organization’s data. It establishes clear policies that ensure data is accurate, up-to-date, reliable, properly formatted, and accessible by the right people. Data governance also enforces the policies that keep data protected, secure, and compliant with regulations such as the GDPR and CCPA.

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The Components of Data Governance

Why Do Businesses Need Data Governance?

Data governance helps organizations mitigate risk and increase operational efficiency so users and AI agents can make confident, data-driven decisions. By providing the guardrails necessary to maintain regulatory compliance and enhance security, governance policies prevent the mishandling of data that can lead to financial and reputational consequences. Further, a centralized governance framework helps organizations minimize data redundancy—reducing manual work and improving the quality of data feeding downstream systems and AI agents.

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Start With Trustworthy Data: 3 Pillars of Responsible AI

What Is the Difference Between Data Governance and Data Management?

Data governance falls under the broader umbrella of data management and provides the overarching authority that guides all data management operations. Data governance establishes the rules and policies that define data quality standards, access rights, and security and compliance protocols. Data management focuses on the implementation of those rules and policies by managing the day-to-day collection, storage, processing, quality, and protection of the data across its lifecycle

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First-party vs. Third-party Data

How Does AI-Powered Enrichment Differ From Traditional MDM or ETL Tools?

An AI-powered approach to data enrichment differs from that of traditional MDM or ETL tools, such as Informatica, Semarchy, or Stibo, because enrichment is embedded at the core of the data mastering process from the start. Features such as verified match and always-on enrichment pipelines ensure that records remain accurate, enriched, and up to date in real time without the need for coding or custom builds.

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8 Essential Platform Capabilities a Modern MDM Solution Needs

What Business Problems Does Data Governance Solve?

Data governance helps organizations overcome challenges caused by inconsistent, inaccurate, or conflicting data. Data governance also safeguards organizations from financial, operational, and reputational risks caused by the mishandling of sensitive data or noncompliance with regulatory mandates. In addition, by establishing the policies that keep data clean, secure, and compliant, data governance ensures that the data feeding AI systems is high-quality and safe for use.

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AI in Data Governance: Improve Compliance, Control, and Trust

Key Takeaways: Data Governance

  • Data governance establishes the rules, processes, and roles that safeguard an organization’s data. 
  • Data governance helps organizations mitigate risk, increase operational efficiency, and make better data-driven decisions. 
  • Data governance policies and processes work in concert with data management operations to improve and protect enterprise data.
  • Data governance helps organizations avoid financial, operational, and reputational risks caused by incorrect, conflicting, or mishandled data.

Data Governance FAQs

How does Tamr’s MDM solution compare to traditional data governance tools?

Tamr’s AI-native MDM solution complements data governance tools such as Collibra, Alation, and Microsoft Purview by delivering the clean, curated, trustworthy data these solutions need to safeguard sensitive information, enforce governance roles and policies, and remain compliant with regulatory mandates.

How does Tamr support data governance?

Tamr provides persistent, unique IDs that link duplicate records and connect related data across systems and silos. Using no-code feedback workflows, Tamr helps data stewards review issues, confirm matches, and validate data. By logging every match decision, record change, and system interaction, Tamr gives governance teams the traceability needed to justify actions and decisions.

Does Tamr support GDPR and CCPA compliance and consent data stewardship?

Yes, Tamr supports GDPR and CCPA compliance. Please refer to our Trust Portal to see all the current certifications. We also offer standard data protection terms as part of our agreements and can review and sign customer-provided DPAs to meet their specific GDPR and other regulatory requirements.

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Related Data Terms
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AI-Native Master Data Management (MDM)

A modern data mastering approach built and centered around AI.

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Guides

Agentic Data Curation

Approach to data curation where AI agents analyze, explain, and resolve data issues.

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Data Products

Data Enrichment

The process of enhancing internal datasets with outside data sources.

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Data Products

Data Governance

Rules, processes, and roles that safeguard organizational data.

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Data Products

Golden Records

Unified, shared, trusted views of business entity data across systems and sources.

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Enrichment

Enterprise Knowledge Graph

Contextualized view of the connections and relationships between business entities.

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Enrichment

Entity Resolution

Data management technique that identifies and matches records across systems.

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Get a free, no-obligation, 30-minute demo of Tamr, and discover how our unique AI-native MDM solution can empower you to deliver data you can trust.

For more information, please view our privacy policy.