Data Governance & Emerging Tech

📘 Module 1: Foundations of Data Governance (1 Hour)

• What is Data Governance? Definitions and scope
• Key pillars: ownership, quality, lifecycle, and stewardship
• Frameworks: DAMA-DMBOK, NIST, ISO/IEC 38505
• Governance vs. management: roles of legal, IT, and business

📘 Module 2: Data Strategy, Classification & Cataloging (1 Hour)

• Aligning governance to business and regulatory goals
• Data inventory and mapping techniques
• Classification of personal, sensitive, financial, and IP data
• Tools for metadata management and data lineage

📘 Module 3: Data Governance & Privacy Regulations (1 Hour)

• DPDP Act (India), GDPR (EU), CCPA (US) implications
• Consent, purpose limitation, access, retention controls
• Records of Processing Activity (RoPA) and DPIAs
• Role of DPOs and cross-functional privacy champions

📘 Module 4: Governance for AI, ML, Blockchain & Cloud (1 Hour)

• Ethical AI: bias, explainability, and algorithmic accountability
• Smart contracts and immutable records in blockchain
• Cloud data residency, encryption, and third-party risk
• AI Act (EU), ISO/IEC 42001, and governance-by-design

📘 Module 5: Controls, Audits & Technology Enablers (1 Hour)

• Access control, retention, and deletion protocols
• Data protection impact assessments (DPIAs)
• Automation tools for policy enforcement and audits
• GRC platforms and AI-powered data governance suites

📘 Module 6: Roadmap, Metrics & Maturity Assessment (45 Minutes)

• Building and scaling a data governance roadmap
• Maturity models (CMMI, NIST tiers)
• Defining success: data quality, compliance, and trust KPIs
• Real-world case studies and best-in-class benchmarks

🔎 Govern with insight — Harness emerging technologies through structured data governance that ensures legal alignment and ethical stewardship.