Data Access
Data Access

Coming soon:
Connect the right users to the right data – without delay

Empower data owners to centrally manage masking, filtering and access controls across sources, simplifying compliance and safely enabling analytics and AI initiatives.

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Key features
and capabilities

Collibra Data Access centralizes data access management and protection, enabling teams to work efficiently with clear visibility and control.

Simplify access without sacrificing control

Save time and maintain oversight by centralizing access controls.

  • Minimize time spent on access management
    Reduce effort and improve visibility by managing access requests and provisioning access to data across Snowflake, Databricks and BigQuery
  • Enhance security and compliance
    Provide the right level of access through role-based controls that protect sensitive data and support regulatory requirements
  • Reduce friction in data access
    Let data consumers intuitively request and receive access, reducing delays and helping them act on data faster

Protect sensitive data with confidence

Protect sensitive data and support compliance without slowing teams down or requiring data owners to create separate views for user groups.

  • Limit sensitive data risks
    Mitigate risk and protect privacy by masking sensitive data fields based on user roles or access purpose
  • Provide the right users with the right data
    Reduce unnecessary exposure with row filtering so users see only the exact subsets of data needed for their tasks

  • Automate data protection using classifications

    Automatically apply masking and filtering based on data classifications (e.g., PII, PHI) to reduce risk and ensure consistent data protection.

  • Query and collaborate on data

    Enable immediate access to data in Collibra Data Notebook, with role-based controls, masking and filtering rules so data consumers can query and collaborate on the data.

  • Track access provisioning activity

    View an audit log for data access provisioning and requests to maintain visibility, reduce errors and support compliance.

  • Maintain consistent user access across systems

    Integrate with Okta and Microsoft Entra ID to simplify user management, security and efficiency. Define access controls once with universal users and groups to enforce consistent security across data sources, accelerating data access.

Learn how to empower self-service access to data without sacrificing control

Featured blog post

Collibra blog

Collibra + Raito: Redefining data access governance for the AI era

Today, we're excited to announce that Collibra has acquired Raito—a pioneering data access governance platform purpose-built for the complexities of modern data and AI ecosystems. This acquisition advances our vision of delivering a single command center for organizations to confidently use data and AI, anywhere, at any scale.

Read the blog post

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Gartner® Magic Quadrant™ for Data and Analytics Governance Platforms

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Collibra recognized as a Leader in The Forrester Wave™: Enterprise Data Catalogs, Q3 2024

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Frequently asked questions

What is data access governance?

Data access governance is the process of managing and controlling access to your organization's data. The goals of a scalable data access governance program are to enhance data security and regulatory compliance, as well as prevent unauthorized access and data breaches.

What is data access control?

Data access control is a subset of data access governance that refers to the methods used to regulate the viewing and use of specific data in a database or other IT system. The control measures can be as straightforward as multi-factor authentication and as complex as advanced encryption algorithms.

How does governing data access help achieve regulatory compliance?

Robust data access governance allows organizations to precisely control the flow and usage of sensitive data, which is necessary to satisfy regulations like GDPR or HIPAA, providing auditable proof of security controls and policy enforcement.

What is the difference between data masking and data filtering?

Data masking is a technique that obfuscates or replaces sensitive data values (e.g., replacing parts of a social security number) to protect them.

Data filtering restricts the records or subsets of data a user is allowed to see.

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