Find data in context to help you deliver results

On your journey to make use of the right enterprise data to deliver on data and AI initiatives, it's common to encounter some critical blockers to success. Reliance on manual processes and low enterprise-wide data literacy, on top of a continuous increase in volumes and shapes of data sources and data ingested across an evolving business, make delivering growth and creating new business models challenging.

When there's a DataOps practice in place to deliver continuous, high-quality trusted enterprise data, focused on enabling collaboration across an organization, you'll be better positioned to drive agility, speed and new initiatives at scale. Central to the practice will be a data catalog tool that will put data in your hands with automated organization and onboarding of content, consistent definitions and self-service management of enterprise data.

Learn about the capabilities that make IBM Watson® Knowledge Catalog the right fit for your data and business analyst team.

Improve data quality

Accelerate time to value by building your data quality program through one tool. IBM Watson Knowledge Catalog interprets data in the business context it is used and helps you to discover and assess data quality for millions of assets, wherever the data resides.

  • Data quality analysis: Measure the quality of your data using 11 dimensions out-of-the-box, and further customize across every value of every row of every record to reflect a column's quality for your business purposes and compliance.
  • Data lineage: Track where data was originated, and how it’s consumed, allowing for more trust when accessing data across a large number of supported sources and destinations.
  • Reference data management: Standardize common values used across applications using a drag-and-drop feature to simplify mapping columns from .csv files to the reference dataset's code, values and description fields.

Manage data privacy and compliance

With an end-to-end catalog, you can enable data privacy and define data policies to describe how the use of overall data, along with sensitive data and personal information, needs to be handled and automated through data protection, data quality and automation rules.

  • Policy management and enforcement: Create policies to describe how sensitive data needs to be handled and automate across the business through data protection, data quality and automation rules.
  • Intelligent file analysis across structured and unstructured data: Manage regulatory compliance and data governance more efficiently through risk assessment, remediation recommendations and audit-ready compliance checks through IBM Watson Knowledge Catalog and IBM Watson Knowledge Catalog Instascan.

Govern data lakes

Decrease time spent and effort by automating the discovery and cataloging of data, helping to reduce risks and accelerate access to all enterprise data using virtualization.

  • Business glossary: Ensure a common terminology is used across the business by leveraging the glossary to support term hierarchies, synonyms, relationships with technical metadata, and any other custom attributes and relationships the organization needs.
  • Automated metadata generation: Reduce the need for users to annotate data manually by using built-in data discovery algorithms that use machine learning to automatically classify the contents of each data set, including names, addresses, zip codes and social security numbers.
  • Discovery: Streamline the process of finding, importing, analyzing and cataloging new data from different sources making it easier to search for, govern and use the data.

Self-service discovery and analysis

Increase accessibility and collaboration, empowering data citizens with quality data faster than ever before. Share insights and awareness of trusted data to drive monetization. Operationalize data for AI, for reduced costs and faster time to value.

  • Workflow: Elevate corporate accountability by allowing data stewards to create, update, review and approve assets, while providing domain expertise to keep users informed of progress at all times.
  • Role-based catalog: Surface business-ready data for data and business analysts to find the right enterprise data available across all databases or applications, search based on their needed context and use data for their projects.
  • Available as a service: Allow users to easily access profiling, glossary, governance and policy enforcement for their analytics needs.
     

Begin tutorial: Explore the self-service capabilities of Watson Knowledge Catalog

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Try IBM Watson Knowledge Catalog

Activate business-ready data for AI and analytics with intelligent cataloging.