Mastering Data Governance with IBM Knowledge Catalog Tool

Establish a holistic data governance framework that treats data as a valuable corporate asset while ensuring data quality, data security, and compliance across the organization.

Compare data governance definitions from Gartner, DAMA, and IBM to highlight its scope. Define governance as authority, control, planning, monitoring, and enforcement over data assets, including structure, use, and security.

Data governance ensures trusted data across the organization, enabling sales campaigns, customer service excellence, compliance, accurate financial reporting, optimized supply chain, and informed human resources decisions.

Implement data governance to ensure data quality and compliance. Maintain security and accountability while enabling informed decision making and scalable, cost-efficient digital transformation.

Explains the DMCC data management body of knowledge and its 11 data domains, including governance, architecture, storage, integration, security, quality, metadata, master data, warehousing, document management, and reference data.

Centralize and organize data assets, metadata, and artifacts with the data governance catalog, providing metadata management, business glossary, policy rules, relationship mapping, collaboration workflows, search and discovery, and audit capabilities.

Discover how the data governance catalog centralizes metadata management into a single repository for data, assets, terms, policies, and rules. Improve discovery and understanding, enabling policy management, collaboration, and auditing.

The data governance catalog acts as a repository for metadata, business glossary, policies, and governance artifacts, enabling metadata management, policy enforcement, data asset discovery, and collaboration within the governance framework.

Explore how category hierarchy, policy hierarchy, and governance rules organize data assets, terms, and policies to enable holistic data governance, discovery, and collaborative governance.

Discover how data governance catalog tools centralize metadata, enable collaboration and workflow, and offer robust search and integration, including IBM Knowledge Catalog on Cloud Pak for Data.

Explore IBM Knowledge Catalog on Cloud Pak for data, a cloud-based metadata repository that automates data discovery, quality, lineage, protection, and governance to fuel AI and analytics.

Accelerate data discovery, enhance data quality, and automate governance with IBM Knowledge Catalog. Improve data literacy with a common business glossary, knowledge graphs, automated lineage, policy management, RBAC, and masking.

Explore IBM Knowledge Catalog, with advanced discovery via natural language queries, llm-powered metadata enrichment, data lineage, automated governance and masking, and flexible deployment for end-to-end data cataloging and self-service insights.

Explore IBM Knowledge Catalog's use cases across data quality, privacy, and compliance, serving as a central hub for data policies and assets, enabling self-service discovery and AI-enabled insights in lakehouses.

Explore the end-to-end business-ready platform in IBM Knowledge Catalog, enabling data quality, governance, and consumption with auto discovering data, auto classifying data, and auto detecting sensitive data, plus policy management.

Explore how categories organize governance artifacts in IBM Knowledge Catalog, enabling hierarchical structures with subcategories, folders, collaborator roles, and visibility controls for governance.

Explore how policies in IBM Knowledge Catalog govern data through rules, sub-policies, and data protection rules within a hierarchical structure, applying to relational data sets.

Explore governance rules in IBM Knowledge Catalog, which are descriptive, non-enforceable criteria that map business objectives and policies to data governance through interconnected, bidirectional relationships.

Explore data protection rules in IBM Knowledge Catalog. Apply attribute-based access control to protect sensitive data, enforce automatic access, and define actions like deny, redact, obfuscate, substitute, or filter.

Explore how business terms in IBM Knowledge Catalog standardize data descriptions, covering contents, sensitivity, subject, and purpose, to ensure clear, consistent column terminology and linked governance rules.

Explore classifications in IBM Knowledge Catalog to tag assets by sensitivity at the column level, using predefined and customizable options to support data protection and governance.

Explore data classes in IBM Knowledge Catalog, categorize data elements by syntax, and automatically assign business terms. See how they enable governance, data quality rules, and custom classifications.

Explore reference data in IBM Knowledge Catalog, including its definition, hierarchy, and relationships, and see how standardized reference data sets and crosswalks improve data governance, quality, and analytics.

Analyze the drivers of customer satisfaction decline using AI-enabled analytics within IBM Knowledge Catalog on Cloud Pak for Data, emphasizing data quality and governance.

Explore a data governance analysis of customer satisfaction decline using IBM Knowledge Catalog on Cloud Pak for Data to identify AI-driven causes and ensure data quality for dashboard insights.

Define data sources and business vocabulary to establish governance. Discover and import data assets for metadata enrichment, profile quality, assign terms, and publish to a governed catalog.

Download the lab data zip from the IBM data and AI live demos repo, unzip it, and inspect predefined governance CSV files to learn their fields.

Explore a customer satisfaction decline analysis use case by downloading and extracting lab files for the define the business vocabulary section, including predefined governance artifacts CSV files.

Create two platform connections in IBM Knowledge Catalog CP4D to provide read-only access to Cloud Object Storage and DB2 Warehouse data for data stewardship and analytics.

Define the business vocabulary and import governance artifacts to build a trusted data governance foundation in IBM Knowledge Catalog, enabling automated metadata enrichment and cataloging.

Define and enforce data governance and protection rules in IBM Knowledge Catalog CP4D, including obfuscating email addresses, redacting phone numbers, and masking US social security numbers.

Master data governance with IBM Knowledge Catalog CP4D by curating and enriching data assets, leveraging a business glossary, data classes, and automated metadata enrichment.

Publish the fully enriched data assets to the business governance catalog for analytics and AI projects, including cloud object storage and data warehouse connections, in a repeatable process.

Augment cataloged data by adding metadata such as classifications, related assets, tags, and reviews to help data consumers understand and trust the content and improve the search engine knowledge base.

Explore a governed data catalog built through the data governance life cycle, delivering accessible, trusted data assets, and review asset details and metadata enrichment to understand content, terms, and protections.