Introduction
Modern enterprises rely on massive volumes of data for decision-making, analytics, and AI innovation. However, without robust data governance and transparent data lineage, even the most advanced data platforms risk compliance breaches, poor data quality, and organizational mistrust. The Data Governance and Lineage Training Course is tailored to equip engineers and data professionals with the critical knowledge and tools to implement governance frameworks, establish traceable data flows, and align with data privacy regulations. With a focus on hybrid, multi-cloud, and real-time environments, this course bridges the gap between technical engineering and enterprise compliance, enabling scalable, secure, and auditable data ecosystems.

Participants will explore how to automate metadata tracking, integrate governance into modern DevOps pipelines, and ensure regulatory alignment across industries. The course uses real-world scenarios and hands-on exercises with platforms like Apache Atlas, Collibra, and DataHub to empower learners to create a resilient data governance infrastructure.

Duration: 10 Days

Target Audience

• Data Engineers and Data Architects
• Data Governance Officers
• Compliance and Risk Management Professionals
• Cloud Data Engineers
• Metadata Managers and Data Stewards
• DevOps and DataOps Teams
• Machine Learning and AI Practitioners
• Business Intelligence Developers

Course Objectives

• Understand the foundational principles of data governance
• Implement automated data lineage tracking across environments
• Manage metadata using data catalogs and governance tools
• Integrate data governance into CI/CD and DevOps workflows
• Ensure data privacy and regulatory compliance
• Monitor and improve data quality and policy enforcement
• Build collaborative governance frameworks
• Design architectures for scalable governance
• Apply governance to ML and AI data pipelines
• Visualize governance KPIs and audit metrics
• Enable real-time and hybrid data governance

Course Content

Module 1: Introduction to Data Governance

• Core concepts and business importance of data governance
• Governance frameworks and maturity models
• Key governance roles and accountability structures
• Policies, stewardship, and compliance alignment
• Aligning data strategy with business goals

Module 2: Data Lineage Fundamentals

• Types of lineage: business, technical, operational
• Capturing data flow from source to destination
• Visualizing and mapping transformations
• Tools for automated lineage capture
• Practical use cases: audit, debugging, reporting

Module 3: Metadata Management and Data Catalogs

• Role of metadata in governance
• Enterprise metadata harvesting techniques
• Evaluating and deploying data catalogs
• Metadata synchronization across tools
• Organizing metadata taxonomies and glossaries

Module 4: Data Quality Management

• Dimensions of data quality
• Techniques for profiling and validation
• Automating quality monitoring and alerts
• Root cause analysis of quality issues
• Reporting data health and metrics

Module 5: Compliance and Policy Enforcement

• Regulatory frameworks: GDPR, CCPA, HIPAA, etc.
• Access control and data masking
• Creating and managing policy rules
• Auditing and forensic tracing
• Data retention and deletion policies

Module 6: Architecture for Scalable Governance

• Reference architecture for governance tooling
• Centralized vs federated governance
• APIs, connectors, and orchestration tools
• Governance across cloud-native and legacy systems
• Event-driven governance design

Module 7: Governance in Data Pipelines

• Inserting governance checks in data flows
• Documenting ETL/ELT transformations
• Integration with Apache Airflow and dbt
• Tracking schema evolution and data changes
• Versioning pipelines for compliance

Module 8: Tools and Platforms for Governance

• Open-source tools: Apache Atlas, DataHub, Amundsen
• Commercial platforms: Collibra, Alation, Informatica
• Integration with cloud providers and data lakes
• Plugin architectures and extensibility
• Tool comparison matrix and best fit

Module 9: Governance-as-Code and CI/CD Integration

• Defining governance rules in YAML/JSON
• Integrating with Git, Jenkins, and GitHub Actions
• Approval gates for metadata and access
• Infrastructure as code for policy automation
• CI/CD pipelines for governance assets

Module 10: Stewardship and Collaboration

• Roles and responsibilities of data stewards
• Workflows for stewardship tasks
• Engaging business teams in governance
• Resolving data ownership conflicts
• Promoting a governance culture

Module 11: Governance for AI and ML Pipelines

• Governance in model training and deployment
• Capturing lineage in ML features and datasets
• Managing bias, drift, and explainability
• Versioning models and audit trails
• Securing synthetic and sensitive datasets

Module 12: Multi-Cloud and Hybrid Governance

• Discovery and classification across cloud environments
• Unified policy enforcement
• Metadata sharing between platforms
• Avoiding silos in hybrid architectures
• Data fabric for consistent governance

Module 13: Monitoring and Reporting Governance KPIs

• Defining governance performance metrics
• Building dashboards for lineage and quality
• SLA tracking for data pipelines
• Reporting for audits and regulators
• Alerting and notification strategies

Module 14: Data Contracts and SLAs

• Designing data producer-consumer agreements
• Schema enforcement and compatibility testing
• Breaking change detection and rollback
• Automating SLAs in data flows
• Enabling reliable data sharing

Module 15: Governance Roadmap and Sustainability

• Establishing short- and long-term governance goals
• Prioritizing based on risk and value
• Change management and stakeholder buy-in
• Scaling governance programs
• Staying current with industry trends and tools

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.