Magic Quadrant for Data and Analytics Governance Platforms

How does Gartner define the Data and Analytics Governance Platforms market in 2025?

A data and analytics governance platform is a set of integrated business and technology capabilities that help business leaders and users to develop and deploy a diverse set of governance policies and monitor and enforce those policies across their organizations' business systems. These platforms are unique from data management in that data management focuses on policy execution, whereas these platforms are used primarily by business roles — not only or even specifically IT roles. The work of data and analytics governance includes policy setting and policy enforcement, and excludes data management (policy execution). Use cases are employed across numerous governance policy categories and multiple business scenarios. The intersection of use-case and policy categories is then used to identify the technology capability.

Key Facts for Magic Quadrant for Data and Analytics Governance Platforms in 2025

Publication Date: 7 January 2025

Document ID: G00807073

Coverage: Global

Authors: Guido De Simoni, Anurag Raj, and 2 more

Core Purpose: A data and analytics governance platform will help business and tech leaders to design, implement and monitor governance policies. As end users increasingly demand the simplification and unification offered by this emerging platform, D&A leaders should explore and adopt these capabilities to meet their evolving needs.

How was the Data and Analytics Governance Platforms market evolved in 2025?

The market for D&A governance platforms is growing at 15% faster than other data-related segments

D&A governance platforms grew alongside the broader data-related segment which reached $114.4 billion in 2024 with 12.8% growth

This is an emerging market with most vendors (Niche Players) still focused on data management rather than comprehensive data and analytics governance

Only 3 Leaders in the market: Collibra, IBM, and Informatica

3 Visionaries identified: Alation, Atlan, and data.world

No Challengers identified in this emerging market due to relatively low overall customer base

Organizations are shifting from siloed governance initiatives to unified platforms supporting multiple policy dimensions

Growing demand for converged D&A governance platforms that address policy setting, execution and enforcement across all policy types

Market characterized by confusion due to overlapping terminology and capabilities across different vendor solutions

Key trends include platform convergence with metadata management, consumerization for diverse personas, AI governance capabilities, and augmented stewardship using GenAI

What product features are required to be included in this year's evaluation?

Work of policy setting — Operationalize, serve and automate the work of the governance board in policy setting.

Work of policy enforcement — Operationalize, serve and automate the work of the data and analytics steward (business role) in policy enforcement.

What are the common features of top products in the Data and Analytics Governance Platforms space?

Access management — Set up and assign roles, organization relationships, and user access privileges for functions related to D&A governance.

Active metadata — This involves the continuous analysis of all available user, data management, systems/infrastructure and data governance experience reports to determine the alignment and exception cases between data as designed versus actual experience.

Business glossary — This refers to the ability to develop and use a glossary in support of policy analysis and development. It includes the ability to support taxonomies and ontologies to address semantic variations.

Connectivity/integration — This refers to the capability to provide facilities for loading (import) and exporting metadata, including roles, in a fast, efficient and accurate manner with other third-party tools.

Data catalog — This is the ability to inventory and curate data assets. Data inventory capabilities are enabled by machine learning (ML) and automatic detection of relationships with other data assets.

Data classification — Data classification is broadly defined as the process of organizing data by relevant categories so that it may be used and protected more efficiently.

Data dictionary — A data dictionary (technical metadata) is a collection of names, definitions and attributes about data elements that are being used or captured in a database, information system or as part of a research project.

Data lineage — This capability includes the depth and breadth of data lineage for identifying data provenance.

Impact analysis — This capability includes impact analysis to identify the impact of a change on any metadata element.

Information policy representation (high level) — This refers to a place to model, store and access (for state and/or persistence) a business representation of the governance policies being enforced.

Matching, linking and merging — This is the matching, linking and merging of related data entries within or across diverse datasets using a variety of traditional and new approaches.

Model management — This is the ability to review, edit, explore and otherwise interrogate various models (data, policy, rule, organizational, etc.) and various states and conditions over time.

Orchestration/automation — Orchestration/automation comes with augmented data management. Augmented data management uses ML to automate various activities.

Organization and role models — This is the ability to set up organizational models and associated user IDs with key roles across the various workflows.

Profiling — This refers to the statistical analysis of diverse datasets (ranging from structured to unstructured data and from internal to external data) to give business users insight into the quality of data.

Rule management (low level) — This capability automates the enforcement of business rules that are tied to data elements and associated metadata.

Security (on the platform itself) — This refers to the provision of certain data security policies through data risk assessment and orchestration of data security controls.

Tag management — The solution should possess enrichment capabilities through user tagging of content or automatic detection, such as personally identifiable information/data (PII or PID).

Task management — This refers to the ability to set up, assign and reassign tasks across the organizational roles involved in policy setting, enforcement and external roles/users.

User interface (as support for all governance-related roles) — This refers to the ability to support the skills and needs of a variety of roles and provide them with collaborative workflows.

Workflow management — These capabilities include business process modeling, data flow modeling and documentation, and support for analytics key performance indicators (KPIs) and other benchmarking efforts.

Scope Exclusions

Data management (policy execution) is excluded - focus is on policy setting and enforcement only

Solutions that do not demonstrate integrated platform capabilities across the inclusion criteria

Vendors without at least 25 paying production customers

Solutions not available in general availability by 1 June 2024

Vendors without presence in at least two geographic regions

Solutions that do not support at least five different user types

Vendors without customer base spanning at least three industry sectors

Inclusion Criteria

Vendors must, among other requirements:

Offer stand-alone platform solutions positioned, marketed, and sold specifically for general-purpose data and analytics governance applications

Demonstrate general availability (GA) from 1 June 2024

Operationalize and automate the work of policy setting and policy enforcement with required standard capabilities

Support augmentation of at least five capabilities by leveraging AI/ML features

Enable large-scale deployment via runtime architectures supporting concurrent users and applications

Include complete solution for five or more types of users (data steward, data architect, data quality analyst, etc.)

Support integrability and interoperability with other data management solutions from third-party tools

Demonstrate in at least three scenarios how the platform operationalizes and automates policy setting, enforcement and execution

Maintain at least 25 paying production customers for flagship data governance initiative

Provide direct sales and support operations in at least two regions

Rank among top organizations in Customer Interest indicator (CII)

Customer base must include paying customers in at least five countries and two or more regions

Customer base must be representative of three or more industry sectors

Ability to Execute — Relative Weighting

Product or Service - Medium

Overall Viability - Medium

Sales Execution/Pricing - Low

Market Responsiveness/Record - High

Marketing Execution - Medium

Customer Experience - Medium

Operations - Medium

Completeness of Vision — Relative Weighting

Market Understanding - High

Marketing Strategy - High

Sales Strategy - Medium

Offering (Product) Strategy - High

Business Model - Medium

Vertical/Industry Strategy - Medium

Innovation - High

Geographic Strategy - Medium

FAQs

Q: What does this research cover?

A: This research evaluates vendors that provide data and analytics governance platforms - integrated business and technology capabilities that help business leaders and users develop, deploy, monitor and enforce governance policies across their organizations' business systems. The research specifically covers platforms focused on operationalizing and automating the work of policy setting and policy enforcement (not policy execution/data management). The evaluation includes 18 vendors across mandatory features like access management, active metadata, business glossary, data catalog, data lineage, workflow management and other common governance capabilities.

Q: Who should use this research?

A: Data and analytics leaders who are investing in operationalizing and automating the work of data and analytics governance should use this research. It is specifically valuable for organizations looking to move from siloed governance initiatives (data security, privacy management, data retention) toward a single unified platform that supports multiple policy dimensions. Business and technical leaders seeking to design, implement and monitor governance policies across policy setting and enforcement use cases should evaluate the vendors in this market.

Q: What are the mandatory features of vendors included in this market?

A: Vendors must have two mandatory features: (1) Work of policy setting - the ability to operationalize, serve and automate the work of the governance board in policy setting, and (2) Work of policy enforcement - the ability to operationalize, serve and automate the work of the data and analytics steward (business role) in policy enforcement. These platforms must focus on business-facing governance activities rather than purely technical data management execution.

Q: What are some reasons for not being included in this report?

Product not available in general availability by 1 June 2024 (e.g., Microsoft Purview was excluded for this reason)
Fewer than 25 paying production customers
Lack of presence in at least two geographic regions
Customer base not representative of three or more industry sectors
Inability to demonstrate required standard capabilities (access management, active metadata, business glossary, connectivity/integration, data catalog, data classification, data dictionary, data lineage, impact analysis, matching/linking/merging, model management, orchestration/automation, organization and role models, profiling, rule management, security, tag management, task management, user interface, workflow management)
Lack of AI/ML augmentation for at least five capabilities
Inability to support large-scale deployment with concurrent users
Not supporting at least five different user types with complete solutions
Solutions positioned primarily for data management (policy execution) rather than governance (policy setting and enforcement)
Insufficient customer interest ranking (CII)
Stand-alone component solutions not integrated into a comprehensive platform

Q: What differentiates Ability to Execute vs. Completeness of Vision?

A: Ability to Execute evaluates vendors on the quality and efficacy of processes, systems, methods or procedures that enable IT provider performance to be competitive, efficient and effective, and to positively impact revenue, retention and reputation. It focuses on current operational capabilities including product/service quality, sales execution, market responsiveness, customer experience, and operations. Completeness of Vision covers current and future market direction, innovation, customer needs and competitive forces, and how well they correspond to Gartner's view of the market. It emphasizes strategic capabilities including market understanding, marketing and sales strategy, product strategy, business model, innovation, and geographic reach.

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