Introduction
Building operational excellence at enterprises requires that data quality across several functions are up to date, complete, unique and reliable.
While, a data cleansing exercise can solve this challenge for legacy master data, ensuring integrity in data quality on a continuous basis requires that companies maintain centrally managed data governance policy, a team to manage the evolution of these policies and a software to ensure enforcement and adherence to those policies and introduce automations wherever possible. By implementing the right master data management software solution, companies can maintain a single source of truth, reduce redundancies, and ensure data integrity across systems and processes.
In this list, we compare the leading master data governance tools, their key features, the expertise of the companies that have built them and how they can help build a data-first organization.
Integrity© by Verdantis
Verdantis is an enterprise leader in master data management and asset lifecycle data, with a specific focus in AI-driven MDM and data governance solution.
Integrity© is Verdantis’ flagship product that is purpose-built for seamless data governance and real-time master data maintenance.
Integrity was first launched in 2016 exclusively for building excellence in MRO data governance after popular demand from Verdantis’ customers who were primarily engaging with them over multi-year engagements for cleansing MRO spare parts data.
Instead of having enterprises engage periodically for expensive and laborious data cleansing projects, the company launched this data governance solution to enable enterprises to access clean, complete and reliable data at any given point in time; thus ensuring continued “Integrity” in data quality on an ongoing basis.
Since then, Integrity has evolved into a holistic product that governs master data across MRO [Materials], Fixed Assets, Suppliers & Business Partner and Human Resources.
Given the particular relevance for production-heavy operations, Integrity is popular for enterprises that are into asset intensive operations.
Key Value Drivers
Here are some of the benefits and value propositions that enterprises can benefit from by deploying Integrity:
This is a non-standard feature that generic MDM solutions do not offer; equipment, spare parts and supplier records are often incomplete and haphazardly inputted into the ERP system.
If provided with enough identifiable information; Integrity can autonomously fetch data points like Manufacturer Name, Part Number, Tax Identification Number of the Supplier and several other data points from publicly available data sources and proprietary first party catalogues.
The data enrichment workflow also goes a step beyond and notifies a user when a requested part/equipment/supplier is obsolete/defunct and also suggests alternatives, if available.
Specific add-on agents within Integrity can independently execute tasks depending on user-inputs and the extracted information
For example; an agent can autonomously create a digital record in the ERP from the bills of materials information shared by a supplier for any given piece of equipment; after which, the agent maps the data in the MRO master and creates a new part record if it doesn’t exist in the master already – all without any user-input at all.
These agentic solutions are reasonably flexible and vary depending on industry, taxonomies employed, scope of the project and the defined processes in the organization but they certainly help reduce the need for monotonous user-entries and drive efficiency across the manufacturing supply chain.
All the operational foundations in Integrity are powered by AI-models that have been trained on 50 Million + spare parts, fixed assets and supplier records.
All the way from autonomous data enrichment, data standardization as per accepted Taxonomy standards and duplicate identification with the existing data is fully managed by industry-trained AI models.
Organizations have reported that the de-duplication capabilities at source are some of the most powerful in Integrity since the AI models can “understand” a given record and accurately detect if a duplicate already exists.
Integrations across source systems and popular ERPs are quite straightforward and Verdantis’ technical team supports with these requirements.
Moreover, the software can be used as a bolt-on solution on top of other data governance products like SAP MDG and Informatica
You can schedule a slot using the form below, and we will walk you through our product.
Who Should Consider Integrity?
Integrity is not a generic data governance solution for all enterprises; in fact, it is purpose built for enterprises in Asset-Intensive Industries like Manufacturing, Oil & Gas, Utilities and Chemicals.
Moreover, Integrity has very few features as far as Customer & HR Master Data management is concerned and is primarily suited for production/manufacturing enterprises.
For a clearer understanding, you can also watch the video that provides detailed information about our platform.
STEP by STIBO Systems
STEP is Stibo Systems’ flagship platform purpose-built to offer centralized governance for product, customer, supplier, and location data – ensuring a single source of truth that powers operational and digital transformation.
STEP was originally designed to solve complex data challenges in the retail and consumer packaged goods (CPG) sectors, enabling consistent, accurate product information across growing commerce channels.
Over the years, it has evolved into a comprehensive multidomain MDM solution that supports enterprises across a wide range of industries including manufacturing, distribution, life sciences, and financial services.
The platform stands out for its focus on collaborative data governance, ensuring that both IT and business users can steward and enrich master data through intuitive workflows—thus helping companies make better decisions and improve business outcomes at scale.
Since its early days, STEP has gained popularity in global operations requiring omnichannel consistency and global data compliance – particularly in enterprises managing high-volume, high-complexity master data across geographies.
Key Value Drivers
By deploying STEP; organizations can expect the the following Value Drivers
Unlike conventional MDM solutions that are often controlled solely by IT, STEP is designed to democratize master data. It empowers business users through user-friendly interfaces and governance workflows, enabling data stewardship at the point of use.
STEP’s workflow engine allows teams across the organization – procurement, supply chain, compliance, finance – to collaborate in real time on the same master data assets.
This business-first approach reduces bottlenecks and accelerates time to insight.
STEP provides an out-of-the-box framework to manage multiple data domains in a single platform—Product, Customer, Supplier, Asset, and Location. This multidomain approach ensures consistency across all points of data consumption.
The platform is scalable both vertically (depth in a specific domain like product data) and horizontally (across domains), making it a robust choice for enterprises undergoing digital transformation or ERP consolidation.
A key differentiator of STEP is its powerful Product Information Management (PIM) capability, making it the go-to solution for enterprises with complex product hierarchies, catalogs, and global e-commerce operations.
STEP allows for dynamic product modeling, digital asset management, and channel-specific syndication to ensure consistent, high-quality product content across websites, marketplaces, mobile apps, and physical stores.
STEP’s data validation engine enforces rules, formats, and business policies in real time – enabling high data quality at the point of entry and throughout the lifecycle of the data. Built-in dashboards and audit trails help enterprises monitor anomalies, flag outdated or non-compliant records, and maintain data integrity.
Additionally, STEP supports regulatory compliance needs such as GDPR, UDI (Unique Device Identification), and industry-specific standards with ready-to-deploy models and reporting features.
STEP’s open API architecture makes it easy to integrate with popular ERPs (SAP, Oracle), CRM systems, digital commerce platforms, and data lakes. It fits seamlessly within a larger enterprise data stack and can serve as a data backbone for companies orchestrating data across multiple channels and systems.
Moreover, Stibo Systems has built a partner ecosystem and a growing library of accelerators to support faster implementations in industries like retail, manufacturing, and healthcare.
Stibo Systems offers pre-configured data models, taxonomy libraries, and deployment accelerators tailored for specific verticals – enabling faster time to value. Whether managing GDSN compliance in retail or structured BOM data in manufacturing, STEP is adaptable to industry-specific governance needs.
TIBCO
TIBCO Software, now part of Cloud Software Group, is a long-standing enterprise player in integration, analytics, and data management.
Its EBX™ platform is a unified solution for Master Data Management (MDM), Reference Data Management, and Data Governance -designed for high flexibility and multidomain governance.
EBX is TIBCO’s flagship data management platform, enabling enterprises to govern, manage, and share any kind of data asset—whether it’s customers, products, suppliers, locations, or hierarchies—from a single, cohesive environment.
The product originated from Orchestra Networks (acquired by TIBCO in 2018), where it was developed as a next-gen data management hub. Unlike tools that evolved from pure MDM or PIM roots, EBX was built ground-up as a multidomain and model-driven platform, offering a metadata-first approach to data governance.
Today, TIBCO EBX is favored by global financial services, life sciences, public sector, and manufacturing organizations for its strong data governance workflows, collaborative features, and ability to handle complex data models across the enterprise.
Key Value Drivers
Tibco is globally popular because its clients have noted that they deliver on the following fronts;
EBX consolidates Master Data Management, Reference Data Management, and Data Governance capabilities into a single platform. This removes the need for point solutions and ensures consistent rules, processes, and visibility across data types.
Whether it’s managing financial hierarchies, customer domains, product taxonomies, or regulatory reference sets, EBX’s shared governance model supports all these functions cohesively.
A standout feature of EBX is its metadata-driven architecture. This allows organizations to define data models, rules, validations, and workflows without writing custom code.
Business users and data stewards can easily configure new data domains, change validations, and implement business rules using a visual modeling layer- making EBX both highly flexible and low-code.
This agility makes EBX especially useful for organizations where data structures evolve rapidly or require tailored governance models for compliance and auditability.
EBX emphasizes governance through process and control, featuring powerful built-in workflow capabilities. Data stewards, business users, and IT teams can work together through role-based workflows for data creation, validation, enrichment, and approval.
The platform also includes versioning, audit trails, and role-specific views, ensuring that governance processes are transparent, compliant, and collaborative.
TIBCO EBX supports regulatory data governance needs such as BCBS 239, GDPR, HIPAA, Solvency II, and more. It offers granular access control, policy enforcement, and traceable data lineage, which are vital for compliance-heavy industries like banking, insurance, and pharmaceuticals.
The platform can be extended with risk scoring, stewardship SLAs, and exception reporting to manage sensitive or critical data assets with enhanced oversight.
A key usability feature is EBX’s self-service portals for data consumers, enabling them to search, view, and request data assets. This democratizes access to governed data while maintaining control through permissioning and workflow oversight.
Data lineage and impact analysis views further assist data stewards in maintaining trust and accuracy across the data lifecycle.
EBX handles complex hierarchies, recursive relationships, and multidomain models with ease. Whether you need to build a unified customer hierarchy, manage organizational charts, or oversee financial consolidations, EBX can model and govern these relationships intuitively.
Its hierarchy management and version control features are particularly valuable for enterprises managing dynamic and multi-layered data structures.
Kodiak Hub
Unlike other platforms in this list, KodiakHub is not a specialist in master data but is more of a supplier relationship management platform, one that integrates with spend management platforms, ERPs, supplier portals etc and even spreadsheets and live documents.
Founded in 2016 and headquartered in Stockholm, Sweden, Kodiak Hub has expanded its reach across Europe and recently into the U.S. market, serving over 250,000 suppliers across more than 20 industries
Kodiak Hub uses AI and machine learning algorithms to generate dynamic supplier risk and performance scores.
These models analyze a combination of internal metrics, historical data, external risk indicators, and even sustainability data to provide contextual, evolving scorecards – helping teams proactively manage underperformance or risk exposure.
Key Industries Served
Kodiak Hub serves over 20 industries, particularly those with complex, regulated, or high-risk supply chains. Their AI-powered SRM platform is widely adopted across:
Manufacturing & Industrial
Automotive & Mobility
Chemicals & Energy
Food & Beverage
Technology, Electronics & Telecom
Pharmaceuticals & Life Sciences
Retail & Consumer Goods
Construction, Engineering & Infrastructure
Mining, Metals & Natural Resources
Logistics, Transportation & Utilities
Key Features
Kodiak Hub’s platform offers several features that are particularly advantageous for these sectors:
AI Powered Supplier Profiles
Aggregating data from various sources to provide comprehensive supplier insights.
Risk Management Tools
Identifying and mitigating potential supplier-related risks.
Performance Dashboards
Monitoring supplier KPIs and performance metrics.
Compliance Management
Ensuring suppliers meet industry-specific regulatory requirements.
Sustainability Tracking
Assessing suppliers’ environmental and social governance (ESG) practices.
These features enable organizations to make informed decisions, enhance supplier relationships, and drive operational efficiency.
SAP MDG
SAP MDG deserves a spot in this list simply because of its seamless integrations within the SAP ecosystem, a very important benefit for SAP loyalists.
The software was originally built keeping in mind the data quality challenges faced by leading enterprises and while there aren’t any features specific to managing Vendor data, the generic data consolidation, rule-based frameworks and user access controls are quite useful for enterprises exploring supplier data management solutions.
The software natively integrates with SAP Business Partner Object in S4/Hana and ECC and can manage supplier data across SAP & non-SAP source systems.
Here are some additional key features that makes MDG a worthwhile consideration
Key Features
Data Quality Considerations
The software has built-in duplicate detection capabilities, configurable validation rules and address cleaning/standardizing capabilities based on the taxonomies setup.
Third Party Integrations
For supporting supplier data enrichment, validation and de-duplication efforts, built-in integrations with industry-standard databases like D&B and Bureau van Dijk. Moreover, it also integrates with other products within SAP ecosystem like Fiori, Ariba etc for bi-directional data synchronization and enabling automations across supplier-driven processes.
Centralization of Supplier Data
The software’s mutli-lingual capabilities and compatibility with non-SAP source systems means that vendor data across plants, production facilities and be consolidated, centralized and governed to ensure it’s integrity.
Audit Trail & Versioning
SAP MDG allows for a full audit history of data changes, useful for compliance and governance. Supports version comparison and rollback where needed.
Collibra
Collibra is a global pioneer in data intelligence and governance, offering a cloud-native platform focused on driving trusted data access, governance, and compliance across the enterprise.
The Collibra Data Intelligence Platform is the company’s flagship solution, purpose-built to help organizations understand, manage, and trust their data assets through centralized governance, lineage tracking, and role-based stewardship.
Collibra was founded with a vision to bridge the gap between IT and business users in managing enterprise data. Its original success was in metadata management and data stewardship – primarily for regulated industries. Over time, it evolved into a full-scale Data Intelligence Platform, now widely adopted across sectors like financial services, healthcare, retail, and telecom for robust data governance, data cataloging, and compliance.
What sets Collibra apart is its business-first approach, enabling non-technical users to participate in data governance via collaborative workflows, intuitive dashboards, and contextual metadata — helping enterprises shift from raw data to actionable insights.
Key Value Drivers
Collibra is globally popular because its clients have noted that they deliver on the following fronts;
At its core, Collibra offers a comprehensive data governance layer – spanning data definitions, ownership models, policies, and stewardship workflows.
From cataloging datasets to assigning data ownership, the platform ensures that every data element is traceable, governed, and trusted, which is critical for initiatives like digital transformation, self-service analytics, and AI readiness.
Collibra’s Business Glossary and Data Dictionary modules help ensure semantic consistency across departments, preventing misinterpretations and silos.
One of Collibra’s standout features is its unified Data Catalog, which brings together technical metadata, business context, and data quality metrics in one interface.
Users can browse available datasets, understand data lineage, and evaluate data quality scores before making decisions.
The automated lineage mapping helps track data flows from source systems through ETL pipelines to BI dashboards – enhancing transparency and reducing risk.
EBX emphasizes governance through process and control, featuring powerful built-in workflow capabilities. Data stewards, business users, and IT teams can work together through role-based workflows for data creation, validation, enrichment, and approval.
The platform also includes versioning, audit trails, and role-specific views, ensuring that governance processes are transparent, compliant, and collaborative.
Through its acquisition of OwlDQ, Collibra introduced AI-powered data quality monitoring directly into the governance fabric. This allows enterprises to detect anomalies, enforce quality rules, and proactively identify data issues – without requiring extensive configuration.
Data consumers can view data quality insights directly from the catalog, while data engineers can investigate root causes using anomaly detection tools.
The platform is cloud-native and multi-tenant, offering high availability and elastic scalability. It integrates seamlessly with major cloud data ecosystems such as Snowflake, Databricks, AWS, Azure, and Google Cloud.
Whether managing data lakes, warehouses, or streaming platforms, Collibra provides the governance glue across distributed environments, making it a reliable solution for hybrid data landscapes.
Collibra offers deep integrations with systems like SAP, Salesforce, Tableau, Power BI, Informatica, Alation, and more.
This allows data to flow from source to consumption while preserving context, policies, and lineage.
Its open APIs and SDK enable further customization, embedding Collibra functionality within broader data platforms and governance stacks.
Conclusion
Master data Governance is far too broad for one single software solution to solve data management challenges across several industries, functions and role-specific requirements. There are many sap master data governance tools, that are compatible with the SAP ERPs and that organizations can opt for.
That being said, AI/ML capabilities are changing the landscape of data governance with several enrichment, normalization, transformation and integration options built-in and enterprises need to weight their tech-stack and evaluate these software solutions based on their individual merit and the value it drives, depending on the nature of operations and organizational requirements
