Data Governance Masterclass

Define strategy via interviews, vision, and maturity assessments to map the current state to a ROI roadmap. Enablement prepares people, processes, technology; implementation operationalizes governance with KPIs, SLAs, and regulations.

Define and formalize the operating model to align data governance with business strategy, establishing roles, processes, and tools for data stewardship, quality, security, and cataloging.

Learn the essential data governance work products in the enablement phase, including execution strategy, charter, policies, KPIs, and data quality and privacy standards.

Discover how a data governance office organizes a program with an executive steering committee, data governance council, working groups, and data stewards to manage policies, security, and data domains.

Learn how a data governance charter defines the data governance committee's purpose, scope, responsibilities, goals, membership, expected results, start date, and authority to improve data quality.

Learn how to implement a data governance program by building the necessary structures, processes, and policies; explore real-world artifacts, and address challenges aligned with your organizational goals.

A business glossary creates a common language that reduces ambiguity across the organization. It anchors data governance by clarifying terms, supports security classifications, and enables consistent data element labeling.

Discover how a data catalog acts as a centralized repository of data assets and metadata, providing a unified view. Enable discovery, understanding, and secure use across sources.

Explore how a data dictionary defines data elements and attributes, supports data quality, and guides stakeholders by documenting names, types, sizes, values, and relationships.

Trace data lineage from source to current state, including transformations and flow, to boost data governance and quality, support GDPR compliance and troubleshooting, using Informatica, Atlan, Collibra.

Explore how data governance drives data quality through profiling, cleaning, standardization, validation, data quality checks, and monitoring, and learn to assess and maintain accuracy, completeness, consistency, timeliness, validity, and uniqueness.

Define data stewardship within data governance across the data lifecycle, ensuring accuracy, completeness, security, privacy, and regulatory compliance. Drive trusted data usage and accessibility to enable a data-driven culture.

Organize data hierarchically into categories and subcategories with attributes to improve data discovery, access, and governance. Explore top level categories such as customer, financial, and product data, and maintain relationships.

Master data management anchors data governance by creating, cleaning, and maintaining the golden record to ensure data quality, consistency, and a single version of truth across systems.

Explore how data privacy and security underpin data governance by protecting personal information, enforcing subject rights, data minimization, encryption, access controls, and ISO/IEC standards.

Explore practical data governance use cases across roles—from executives to data scientists—using glossary, classification, data catalog, lineage, data quality, and privacy to ensure compliance, integrity, and risk management.

Gain a practical understanding of data governance and apply best practices to improve decisions, processes, and data quality in your work, while staying up to date with the latest developments.