Provide a single location to find, understand and create a shared language around data. With Collibra Data Governance, you can operationalize data governance workflows and processes to deliver trusted data across your organization. And if you're starting your AI journey, knowing where to start with AI governance is key. Learn more about how we put the (data) intelligence in AI.
Define the terminology, rules and regulations that matter to your business so that everyone is on the same page.
Stewardship management
Assign roles and responsibilities, allowing data stewards to share, protect and improve your data assets.
Reference data management
Reconcile data between systems for more accurate reporting and analysis. Identify missing records and broken relationships as you move data across systems.
Centralized policy management
Create, review and update data policies to ensure adoption and maintain compliance across your business.
Intuitive workflows
Interact with common workflows and processes to facilitate a collaborative approach to governance.
Embedded privacy by design
Reduce the cost of compliance as you incorporate privacy into all of your data activities.
Data dictionary
Document your metadata with details about its origin, format, use, structure and relationship to other data.
Data helpdesk
Raise, manage and resolve issues by involving the correct stakeholders to increase trust in data.
How data governance improves your business
Collibra automates governance activities and provides cross-functional teams with a single location to find and establish a common understanding of data.
Quickly find, understand and govern your data
Leverage a single platform to get full visibility into business-critical data assets, including metrics, reports, APIs, models, data products and technology assets, with full business context attached.
Drive a common language around data to speed decision making
Build a business glossary to ensure clarity and consistency of critical business definitions and metrics. Create a shared language for data within your organization so that everyone has a single source of truth.
Leverage automation to keep pace with change
Blend machine learning and human intelligence to add and improve context around data assets. Automate your tasks so governance practices stay up to date as your business evolves.
Mobilize your workforce to encourage collaboration
Enable data stewards to join forces with subject matter experts and data owners through automated workflows, role-based dashboards and interactive views. Automate processes with out-of-the-box and customizable workflows for common governance and stewardship processes.
Ensure compliance and mitigate risks
Scale compliance processes more easily and efficiently, giving your business the confidence to trust authoritative data sources. Automatically find, categorize and map sensitive information. Understand where your data is coming from and how it is used with technical and business lineage.
Customer stories
Healthcare
Froedtert & Medical College of Wisconsin transforms patient experience with Collibra
Financial services
Equifax uses data to bring new products to market
Retail and consumer goods
HEINEKEN relies on data to become the best connected brewer
Data governance is a strategic framework for managing data assets, including ensuring data quality, accessibility, and security. It involves defining policies, processes, and roles for data handling, enhancing decision-making, and regulatory compliance. Effective data governance improves data consistency, collaboration, and trust, reducing errors and risks. By aligning your business goals with data management, data governance enables organizations to unlock the full potential of your data.
Data governance and data management are distinct yet related. Governance oversees data availability, usability, integrity, and security within an organization by setting policies and procedures for data handling. Management involves the practices and technologies for storing, organizing, and managing data, including data modeling, mining, and warehousing. While governance manages data as a strategic asset, data management concentrates on technical aspects of data storage, organization, and access.
To start, consider your organizational goals, size, and industry needs. Next, assess your requirements for ease of use, scalability, and system compatibility. Robust data governance solutions include a data catalog (a searchable inventory of datasets with metadata and lineage for easy organization and understanding), data quality management for accuracy, consistency, and completeness, enabling informed decision-making; and policy management and enforcement that streamlines compliance and security.
A data governance framework aligns organizational goals and challenges to achieve measurable, scalable results and is supported by four key pillars. The four pillars of data governance include distinct use cases connecting governance to business outcomes; quantifiable value for assessing success; targeted product capabilities empowering teams through data discovery, collaboration, and access; and a delivery model that supports scalable service for all your data-intensive use cases.
