The Forrester Wave™: Data Governance Solutions, Q3 2023

Data Governance Solutions Vendor Product Comparisons 2023

Key features and pros and cons of top Data Governance Solutions products:

Alation - Leaders

Pros:

Intelligent federated governance approach with AI-fueled automation
Strong machine learning and intelligent asset classification capabilities
Obsessive focus on collaboration tools and data valuation models
Ability to empower flexible federated governance model on technical and business level
Best-in-class data discovery and cataloging capabilities
Strong lineage and collaboration tools
Extensive training programs and client community building for data literacy

Cons:

Risk of offering becoming expensive in combination with external solutions
Needs continued investment in native integrations for data quality and observability
Platform documentation needs improvement to complement training programs

Collibra - Leaders

Pros:

Strong policy management and compliance capabilities to support stewardship role
Unified intelligent data platform catering to full range of governance personas
Strong business persona, value creation, and collaboration focus
Above-par capabilities in workflow automation features
Full-service model with consistent investments in core technical capabilities (profiling, data quality, lineage)
Breadth of native integration ecosystems
One-stop-shop governance solution for complex data discovery to data product journey use cases

Cons:

Platform can be too customizable, leading to confusion for business users
Cumbersome manual tasks for data engineers
UI is somewhat dated
Needs to integrate acquired solutions more seamlessly with existing databases

BigID - Strong Performers

Pros:

Excels in automated discovery and data privacy capabilities
Strong automated data privacy and protection capabilities spanning governance functions
Strong data discovery, classification, curation, and policy management
On-par lineage extraction and management with easily customizable features
Quality of client engagement and roadmap communication
Best for complementing existing stewardship capabilities while accelerating data discovery and classification

Cons:

Falls short on smooth UX for data stewards
Lacks transparency on pricing strategy with clients losing track of base offering features
Lags on seamless UX journey requiring navigation through app-based features
Missing some native targeted remediation functionalities like data masking
Gaps in native enrichment capabilities
Lack of granular reporting options for precision and value metrics

Informatica - Strong Performers

Pros:

Mature end-to-end solution with intelligent AI-powered metadata engine (CLAIRE)
Vast library of data integrations
Strong data quality and stewardship management functionality
Covers complex range of use cases from enterprise asset classification to unstructured data discovery
Superior roadmap with operational feature enhancements through intelligent automation
Proven track record and practical approach to data democratization

Cons:

Needs to modernize on collaboration features
Needs to upgrade foundational strengths with enhanced collaboration pathways
Lacks customized visualization options and data valuation tools
UX needs improvement
Central role-based customization needs enhancement
Introduction of adoption metrics needed

OneTrust - Strong Performers

Pros:

Strong focus on responsible data use and customer trust
Intuitive platform with extensive global regulatory research database
Access to in-house researchers and experts for data regulation guidance
Ability to discover and manage unstructured data as core offering
Strong privacy and security features
Strong regulatory compliance foundation
Solid policy management capabilities across range of use cases
Almost 300 approved data- and security-related patents by mid-2023

Cons:

Needs to improve data quality granularity
Stewardship workflows need enhancement
Collaboration features need improvement
Needs to seamlessly connect workflows and usability at process and UI levels
Adoption strategy and implementation support must focus more on hands-on ongoing guidance and business value creation

IBM - Contenders

Pros:

Strong cataloging and glossary capabilities
Robust stewardship workflow management
Pre- and post-implementation support
Reliable self-service marketplace functionalities
Accessible self-service cataloging experience
Strong data marketplace capabilities

Cons:

Lags on technical innovation and platform cohesion
Falls short on innovation strategy, focused on catching up rather than exploring collaboration features
Falls behind on seamless UX experience and intuitive navigation
Technical robustness below par for data quality automation and granular issue remediation
Role-based UX customization for data and ML engineers below market standards
Lacks basic collaboration features
Challenge creating modern, collaboration-oriented community

SAP - Contenders

Pros:

Strong data quality features
On-par stewardship control panels
Can be deployed as standalone governance solution outside SAP environment
Successful ML-driven innovation program
Extensive network of development and co-innovation centers worldwide
Large partner ecosystem and loyal customer base
Logical option for enterprise customers using SAP as core ERP engine

Cons:

Confuses with intertwined offerings - strategy needs to be clearer and more independent
Data governance roadmap blurred into general data management investments
Ability to access core governance functionalities is blurred by overlapping data fabric offerings
Some functionalities provided by external integrated partnerships rather than native
Declined to participate in full Forrester Wave evaluation process

FAQs

Q: Which vendors are Leaders in 2023?

A: Alation, Collibra

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders in the Forrester Wave represent vendors with the strongest current offerings and strategies in the data governance solutions market. These vendors demonstrate excellence across key evaluation criteria including data discovery and access, data quality and usage, policy management, stewardship management, data collaboration, and data governance management. Leaders also show strong strategic vision, innovation, roadmap execution, partner ecosystems, adoption rates, community building, and pricing flexibility. In this Q3 2023 evaluation, Leaders are characterized by their ability to: provide stable foundations for trusted data intelligence for AI, support stewardship functions through intuitive workflows and advanced collaboration, and empower data democratization by enhancing data literacy and self-service capabilities.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for Data Governance Solutions in 2023

Data Governance Solutions Vendor Product Comparisons 2023

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FAQs

Q: Which vendors are Leaders in 2023?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

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