What's new and changed in IBM Master Data Management

IBM Software Hub Version 5.4.0

A new version of IBM Master Data Management was released in June 2026 with IBM Software Hub 5.4.0.

Operand version: 4.12.43

This release includes the following changes:

New features

This release of IBM Master Data Management includes the following features:

Optimize matching algorithms by using enhanced pair analysis and recommendations

You can now create and manage multiple pair analysis tasks simultaneously and use their results to generate tuning recommendations for your matching algorithm. With these enhancements, you now have greater flexibility in your matching and algorithm tuning workflow. Additionally, you can now:

• Generate algorithm tuning recommendations before data stewards complete all pair reviews.
• Include manual stewardship decisions (such as link, unlink, and potential match decisions) in the calculations that generate your tuning recommendations.
• Visualize tuning outcomes by using confusion matrices, histograms, and pie charts to understand how changes will impact your algorithm before you apply them.
• Request new pair analysis tasks while others remain in progress.
• Delete unnecessary pair analysis tasks or results.

Automate relationship creation in your master data by defining discovery rules

You can now configure discovery rules to automatically establish and maintain relationships between your master data records and entities. Configure conditions and filters that evaluate your master data to discover and create relationships. Discovery rules work across record-to-record, record-to-entity, and entity-to-entity relationships, ensuring that your relationships stay current and consistent.

Find and fix MDM data quality issues more easily

You can now search for and resolve data quality issues in your master data by using the Stewardship tab. Review potential matches that need manual linking decisions and potential overlays that might indicate incorrect record updates. Click an issue to start working on the remediation task immediately. The new streamlined view helps you focus on the issues that need attention so that you can maintain more accurate master data.

Organize MDM data quality issues by using custom tags

You can now create and manage custom tags in IBM Master Data Management to help your team quickly find, identify, and prioritize data quality issues in your master data. Tags work as searchable, color-coded labels that make it easier to organize and track issues across your organization. You can also configure potential overlay workflows to automatically apply tags to the issues that they create, so your data stewardship processes are streamlined.

Protect sensitive data by configuring access to master data

You can now configure how IBM Master Data Management controls user access to data. Access control strategies ensure that only authorized users can access sensitive or confidential information, such as personally identifiable information (PII).

Configure one or both of the following access control types:

• Attribute-based access control (ABAC) protects specific data characteristics, across all data, from unauthorized users.
• Token-based access control (TBAC) uses security tokens to define user access at the row level for each record.

Modernize your master data management by migrating from InfoSphere® MDM Standard Edition or Advanced Edition or InfoSphere Big Match

You can now migrate your existing master data and matching algorithms from IBM InfoSphere Master Data Management (InfoSphere MDM) or IBM InfoSphere Big Match for Hadoop to the IBM Master Data Management service. By migrating, you gain access to modern, cloud-native capabilities and integration with other IBM Software Hub services.

The IBM Master Data Management migration service provides easy-to-use APIs that preserve your data structure and integrity while minimizing downtime. Your master data entities, relationships, groups, and matching algorithms remain intact throughout the migration process. During migration, both systems run in parallel so that you can validate that the service works correctly before you start using it as your production MDM solution.

Control master data entity attribute composition at the field level

When you configure attribute composition rules, you can now define filtering and prioritization logic at the field level by using value-based rules. As a result, you now have finer control over which record attribute values get surfaced to the entity.

Value-based composition rules help you filter low-quality data and construct more accurate, business-aligned entities. You can exclude invalid values like placeholders or dummy data, prioritize specific values in custom order, apply comparison functions to select for conditions such as the longest name or highest score, and create conditional rules that change depending on data conditions.

Prioritize rare matches over common ones in your master data

You can now configure your IBM Master Data Management matching algorithm to score matches based on how common or rare the matched values are in your actual dataset. The algorithm uses your real data distribution to boost scores for distinctive matches and reduce scores for common ones.

For example, matching on the rare last name "Xylander" should score higher than matching on the common name "Smith," because rare matches are more likely to identify the same person. This prevents the algorithm from over-scoring matches on common values like "John Smith" while under-scoring matches on distinctive values like "Hamish Xylander."

Validate and enrich reference data by using code tables

You can now centralize and manage all of your reference data (such as country codes, status values, and product categories) by using code tables. Code tables automatically validate data as it enters your system, store data efficiently by removing redundant display values, and enrich data with human-readable labels in your preferred language when you retrieve it. Code tables also support multiple languages with automatic fallback, ensure data consistency across your application, and let you update reference values without deploying code changes.

Exchange patient data with HL7-enabled healthcare systems

You can now exchange patient data between IBM Master Data Management and your HL7-enabled healthcare systems by using a message broker. Use the HL7 message broker to maintain a single source of truth for patient information across hospital registration systems, electronic medical records, laboratory systems, and other healthcare applications that use the HL7 communication protocol.

This capability is specific to the healthcare industry and is not enabled by default. For more information, see the IBM Master Data Management administration topics.

New features from 5.3.1 patches

This release of IBM Master Data Management includes the following features that were introduced in IBM Software Hub Version 5.3.1 patches:

Modernize your master data management by migrating from InfoSphere MDM Advanced Edition

You can now migrate your existing master data and matching algorithms from IBM InfoSphere Master Data Management (InfoSphere MDM) Advanced Edition to the IBM Master Data Management service. By migrating, you gain access to modern, cloud-native capabilities and integration with other IBM Software Hub services.

Updates

The following updates were introduced in this release:

• You can now set the retention period for historical master data to manage memory usage more efficiently. By configuring how long the system keeps historical events, you can control storage costs while maintaining the data history you need for compliance and analysis.

Issues fixed in this release

This release of the IBM Master Data Management service includes various defect fixes.

Security issues fixed in this release

This release of the IBM Master Data Management service includes various security fixes.