Introduction to Data Governance

Define a data governance program using smart goals—specific, measurable, achievable, relevant, and time-bound. Reduce duplicate customer records by 85% in six months and achieve GDPR audit readiness by quarter four.

Align data governance with business strategy to enable growth, trust, and efficiency. Engage stakeholders and tie governance metrics to business key performance indicators such as customer retention and reporting accuracy.

Explore the roles and responsibilities in data governance teams, from data owners and strategists to stewards, watchdogs, and enablers, and how they align strategy with policy, data quality, and compliance.

Understand data quality as trust in numbers, with dimensions—accuracy, completeness, consistency, timeliness, uniqueness, validity—and metrics such as invalid entries, duplicates, data sync, time to correct errors, and field completion.

Explore root causes of data quality driven by people problems, including unclear ownership, training gaps, and conflicting definitions, and illustrate how governance, validation rules, and a data culture protect accuracy.

Cleanse data to remove duplicates, outdated records, blank fields, and inconsistent formats, then validate with rules to prevent errors and enrich with context for smarter decisions.

Define data governance with clear policies and standards that establish trust, accountability, and consistency across the data lifecycle, roles, and actionable guidance on encryption, retention, naming, and tagging.

Metadata provides the descriptive context that makes data searchable and usable. Cataloging, standardizing, linking, and securing technical, business, and operational metadata supports governance, compliance, and data lineage.

The lecture covers the lifecycle from creation to destruction and shows how lifecycle management and classification with lineage and retention policies strengthen governance, reduce data sprawl, and support compliance.

Examine GDPR and CCPA to understand explicit consent, rights to know, delete, and opt out of data selling, alongside PSD2's open banking and strong customer authentication.

Explore how information security and data governance work together to protect and manage data assets, aligning confidentiality, integrity, and availability with governance and security controls under ISO IEC 27001.

Embed compliance into daily operations to foster accountability and trust, guided by data protection laws like GDPR and internal policies, and implement preventive, detective, and corrective controls.

Discover how data stewards safeguard data integrity by translating, enforcing standards, and monitoring quality in real time, then documenting definitions and collaborating across teams to ensure trusted data.

Assign accountable data owners by domain to define how data should be used, protected, and evaluated. Document ownership in metadata platforms and ensure quarterly reviews to keep governance aligned.

Learn how to turn data governance into a living practice through storytelling, clear communication, and change management that engages stakeholders, trains data champions, and aligns teams around shared goals.

Explore how modern governance tools like Collibra, Alation, and Informatica provide a centralized data catalog, single source of truth, role-based access, and policy workflows to scale data governance.

Automating data governance workflows reduces delays, enforces policies in real time, and scales governance by automating data access requests, data asset certification, and policy enforcement.

Integrate governance into bi, mdm, and data lakes; align dashboards with back-end policies, enable lineage and pii classifications via vetted data catalogs.

Lay a foundation for data governance by clarifying purpose, securing executive sponsorship, and defining roles, domains, and a charter; then implement tools, metadata, and scalable policies, piloting across domains.