IBM Knowledge Catalog is software to manage and curate data, knowledge assets, and their relationships. It is available as managed SaaS or within IBM Cloud Pak® for Data.
IBM Knowledge Catalog is a data catalog tool that powers intelligent, self-service discovery of data, models and more. The cloud-based enterprise metadata repository activates information for AI, machine learning (ML) and deep learning supported by active metadata. Access, curate, categorize and share data, knowledge assets and their relationships, wherever they reside.
Use IBM Knowledge Catalog for IBM Cloud Pak® for Data to deliver business-ready data to feed AI and analytics projects.
Accelerate responsible, transparent and explainable AI workflows for both generative AI and machine learning models
IBM acquires Manta to complement data and AI governance capabilities
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Explore the new data governance and data quality capabilities introduced in IBM Cloud Pak for Data 4.7
Create a common business glossary governance foundation. Customize to meet your requirements for a better data understanding.
Deliver timely, trusted, quality data with ML and automation. Help ensure a well-structured and maintained data lineage.
Active policy management, role-based access control and dynamic masking of sensitive data help protect data to promote compliance and audit readiness.
Find relevant assets quickly and at scale based on intelligent recommendations from IBM Watson® and peers.
Track lineage and quality scores across structured data, unstructured data, AI models and notebooks.
Deploy on premises, on cloud, or fully managed as a service on IBM Cloud Pak for Data.
Organize, define and manage enterprise data to provide the right context and drive value across needs like regulatory compliance and data monetization.
Protect data, manage compliance and audit-readiness, and maintain client trust with active policy management and dynamic masking of sensitive data.
Consume and transform data at the speed of business with intuitive dashboards and flows that can be shared with peers or analytics tools.
Reliance on manual processes, low enterprise-wide data literacy, and the continuous growth of data volumes, types and sources may be hindering your data and AI initiatives. A DataOps practice that delivers continuous, high-quality trusted enterprise data and enables collaboration across your business can position you to drive agility, speed and new initiatives at scale.
Central to the practice is a data catalog tool with automated organization and onboarding of content, consistent definitions and self-service management of enterprise data.
Deploy a unified privacy framework to enhance data privacy and AI protection. Mask sensitive data and automate how you generate metadata, enforce policies and build a business vocabulary.
Deliver high-quality entity data by augmenting metadata management with master data management capabilities. Expand data sources and depth to ensure a single source of truth.
Use AI to intelligently automate the identification, monitoring and enforcement of policies on sensitive data across the organization with AutoPrivacy capabilities on IBM Cloud Pak for Data.
Make data understandable by all who need it with a common business vocabulary. Automatically provide business context with out-of-the-box regulatory and industry glossaries.
Get a unified view of all your private data assets and run privacy assessments on them after loading asset metadata into IBM® OpenPages®.
Get a 360-degree view of critical data entities by automatically matching data from various sources to customer profiles without duplication. Monitor critical data like PII and consent.
Create a read-only view of master data records — a view that is highly available, always on and consistent across IBM Cloud Pak for Data. Avoid data duplication and efficiently access data with low latency.