Making data work smarter: What’s new in IBM Cloud Pak for Data 5.2

The latest release of IBM Cloud Pak for Data—version 5.2—comes with a range of new enhancements focused on usability, data governance and performance. It helps organizations simplify data management, accelerate access to insights and deliver meaningful business outcomes.

Additionally, IBM Software Hub, which is the decoupled platform in an earlier release, offers greater flexibility in deployment and management options.

Enterprises are facing mounting challenges, like data silos, outdated tools, slow insights and rising compliance risks. To stay innovative and make smart decisions, organizations need intelligent, scalable solutions now more than ever.

IBM Cloud Pak for Data 5.2 continues to evolve as a unified platform designed to simplify how organizations collect, organize and analyze data across hybrid and multi-cloud environments. With its modular, containerized architecture, the platform enables teams to start with the essentials and quickly scale, activating only the services they need. Whether leveraging trusted data with Match 360, accessing distributed data through Data Virtualization, enhancing governance with IBM Knowledge Catalog, or analysing data with Watson Studio customers can build a strong data foundation to accelerate AI and analytics.

Version 5.2 brings updates across these core services and more, driving even greater flexibility, performance and insight.

IBM Match 360 introduces powerful enhancements to streamline master data management, including improved tools for remediating potential overlay tasks—featuring an enhanced comparison table and simplified remediation controls that help data stewards confidently resolve updates—and a centralized Data Types screen that allows data engineers to configure and manage all data types in one place, offering complete visibility and control over attribute, entity, and relationship types, as well as custom matching configurations, all from a single, intuitive interface.

Data virtualization is evolving to meet the growing demands of modern businesses, offering powerful new features that enhance data transparency, security, and governance. With the integration of MANTA Automated Data Lineage, organizations can now trace the full journey of their data—understanding where it originates, how it moves, and where it ends up. This visibility supports better compliance, impact analysis, and trust in data. Additionally, the new “Mask at Read” functionality ensures sensitive data is protected even before queries are processed, helping businesses meet strict privacy regulations while maintaining performance.

Further strengthening its capabilities, Data Virtualization now supports Db2 datalake tables, replacing legacy Hadoop tables for more efficient access to Cloud Object Storage. This shift simplifies data management with familiar SQL syntax and improved performance. Meanwhile, the introduction of shared properties across governed catalogs allows for consistent governance of data assets across environments, streamlining compliance and metadata management. Together, these enhancements empower businesses to modernize their data infrastructure while maintaining control, security, and agility.

With the new release of IBM Knowledge Catalog (IKC), IBM now brings native support for IBM Power Architecture, expanding its enterprise data governance capabilities to a wider range of infrastructure environments. Included in IBM Cloud Pak for Data Enterprise Edition, IKC on Power enables organizations to automate data governance processes—ensuring data accessibility, trust, security, and compliance—while leveraging the performance and reliability of IBM Power systems. Key capabilities such as business metadata enrichment, governance artifact management, collaborative project workspaces, centralized catalogs, and secure connectivity to diverse data sources are fully supported, allowing enterprises to unify governance and analytics workflows across x86 and Power platforms.

This release aligns with IBM’s strategic modernization efforts to deliver a consistent, AI-ready data foundation across hybrid cloud environments. While foundational features are fully available, a few advanced capabilities—such as Data Quality, Relationship Explorer, and Semantic Enrichment—are not yet supported on Power and are planned for future updates. Overall, this expansion marks a significant step in enabling mission-critical Power-based workloads to benefit from the same enterprise-grade data cataloging and governance tools used across the IBM Cloud Pak for Data ecosystem.

Additionally, IKC now offers greater flexibility and visibility with execution windows for metadata jobs, indirect relationship views on the explorer canvas, and customizable display names. These enhancements empower users to better understand and control their data landscape while maintaining compliance and security. By enabling more users to participate in governance—even with view-only permissions—IKC fosters a more inclusive and scalable data governance culture, helping businesses unlock deeper insights and drive smarter decisions.

IBM has also introduced powerful new features in Watson Studio and Watson Machine Learning that enhance productivity, collaboration, and deployment for AI projects.

Watson Studio now includes a Document editor for creating and managing project documentation, improving team alignment and organization. It also supports importing and publishing watsonx™ assets in Git-integrated projects, streamlining asset reuse and version control. Meanwhile, Watson Machine Learning enables deployment of models using the latest runtime 25.1 and supports models trained with Spark 3.5, offering improved performance, scalability, and compatibility.

These updates empower businesses to accelerate innovation, reduce complexity, and scale AI solutions more effectively.

With IBM Cloud Pak for Data 5.2, organizations gain a powerful, flexible platform to unify data, enhance governance, and accelerate AI-driven insights. These advancements translate into faster decision-making, reduced risk and a stronger foundation for innovation in today’s data-driven economy.

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