Why Trustworthy AI Is the Key to Unlocking Technology's True Potential

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Overview of Product

IBM Watson Knowledge Catalog empowers organizations to take control of their data while activating AI and analytics across the enterprise. With smart cataloging, seamless data governance, and intelligent policy management, Watson Knowledge Catalog ensures consistent data quality, security, and performance—making it the perfect solution for DataOps practices.

 

Why Choose IBM Watson Knowledge Catalog?

Significantly reduce data discovery, quality checks, and governance times by up to 90%, enabling fast, accurate insights.
Tailor your data governance to your needs with a shared business glossary, ensuring consistent and high-quality data.
Easily trace data lineage, ensuring transparency and trust with a 360-degree view of data origins.
Active policy management, role-based access control, and real-time data masking ensure data protection and regulatory readiness.
Streamlined dashboards and flows for faster access to data and sharing across your organization.
Automate policy identification and enforcement with AI-driven privacy features to safeguard sensitive data.

What the Numbers say?

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90% reduction in time spent on data discovery and quality checks.

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50% increase in data utilization speed across key industries.

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Adopted by over 70% of Fortune 500 companies to streamline DataOps.

Features

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Use smart suggestions powered by IBM Watson® to locate relevant data assets quickly.
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Keep track of data quality across different formats, AI models, and notebooks for consistent performance.
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Choose between on-premises, cloud, or managed via IBM Cloud Pak for Data for tailored solutions.
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Efficiently organize, define, and manage enterprise-wide data for regulatory compliance and greater value.
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Streamline policy management with active enforcement, ensuring compliance and data security.
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Accelerate access to data with intuitive, user-friendly dashboards and analytics tools that encourage peer collaboration.

Key Facts

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IBM Watson Knowledge Catalog is a leading solution for intelligent data governance.

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Provides an end-to-end solution for data discovery, lineage, and governance.

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Offers a 360-degree view of your data, ensuring transparency and trust at every step.

What The Users Say

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Leading enterprises from a range of industries have trusted IBM Watson Knowledge Catalog to streamline their data management processes. By enhancing collaboration and promoting data quality, these organizations have seen marked improvements in their AI initiatives and business intelligence efforts. Join top companies in the quest for optimized data governance.

FAQs

IBM Watson Knowledge Catalog is a metadata management and data governance tool that allows organizations to discover, curate, categorize, and govern data assets across hybrid cloud environments.

The catalog automates data classification and uses AI-powered recommendations to surface high-quality, trusted data assets, reducing search time and improving data usability for analytics.

Absolutely. It provides robust policy enforcement, including role-based access control, data masking, and approval workflows to ensure data is accessed securely and in compliance with internal rules.

Metadata enrichment involves automatically tagging data assets with context such as sensitivity, ownership, and relationships. This is done via AI-driven scanning and lineage tracing, boosting data quality and governance.

The catalog aids in compliance with standards like GDPR and CCPA by allowing organizations to manage sensitive data, apply consent policies, and track data lineage for auditing purposes.

Yes, teams can annotate datasets, assign stewards, share curated assets, and track usage metrics. This drives a data-first culture across departments.

Watson Knowledge Catalog supports structured, semi-structured, and unstructured data across on-premise, cloud, and SaaS platforms, including Db2, Snowflake, BigQuery, Amazon S3, and more.

Resources

Take the first step toward mastering your data with IBM Watson Knowledge Catalog.

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