The Data Governance & Information Lifecycle Management training is a focused two-day program designed to help organizations establish structured governance over data assets while managing data throughout its entire lifecycle. This course explains how data governance frameworks, policies, roles, and lifecycle controls ensure data quality, security, compliance, and value realization, enabling organizations to treat data as a strategic and well-governed asset.

• Understand the principles, governance frameworks, and data lifecycle management practices of Data Governance for organizational  data management.
• Set up and apply data governance frameworks, data quality controls, compliance standards, and lifecycle management policies for  enterprise environments.
• Design data classification strategies, governance models, retention policies, and information management workflows using data  governance approaches.
• Implement data stewardship, metadata management, access control, archival processes, and compliance monitoring workflows  effectively.
• Debug, test, and optimize governance processes, data quality controls, and lifecycle operations for scalability, reliability, and regulatory  compliance.
• Build secure, compliant, and production-ready data governance solutions using industry best practices.

• Data governance and data management professionals
• IT governance, risk, and compliance professionals
• Data architects and data stewards
• Information security and privacy professionals
• Business managers responsible for data-driven initiatives

• Basic understanding of organizational processes and data usage
• Familiarity with IT systems or data management concepts is beneficial
• Awareness of governance, risk, or compliance concepts is helpful
• No prior data governance certification is required

• Understanding data governance principles and operating models
• Ability to define data ownership, stewardship, and accountability
• Knowledge of data lifecycle stages and management controls
• Awareness of data quality, security, and compliance requirements
• Capability to support enterprise-wide data governance initiatives

By the end of this training, participants will have a clear understanding of data governance and information lifecycle management practices. Learners will be able to support structured governance frameworks, manage data across its lifecycle, improve data quality and compliance, and contribute to effective, enterprise-wide data management initiatives.

Introduction to Data Governance Concepts
• Definition and objectives of data governance
• Data as an enterprise asset
• Business drivers for data governance
• Common data governance challenges

Data Governance Frameworks, Roles, and Structures
• Data governance operating models
• Data owners, data stewards, and custodians
• Governance committees and decision forums
• Accountability and escalation mechanisms

Policies, Standards, and Data Classification
• Role of policies and standards in data governance
• Data classification schemes
• Handling requirements for different data types
• Alignment with regulatory and business needs

Data Quality Management and Metadata Governance
• Data quality dimensions and metrics
• Data quality ownership and monitoring
• Metadata management concepts
• Improving trust and usability of data

Information Lifecycle Management Overview
• Data creation and acquisition
• Data usage and sharing considerations
• Data storage and maintenance
• Data archival and disposal concepts

Data Security, Privacy, and Compliance Across the Lifecycle
• Protecting data at each lifecycle stage
• Privacy and regulatory considerations
• Access controls and data protection awareness
• Managing retention and deletion requirements

Data Governance Integration with Business and IT
• Embedding governance into business processes
• Alignment with IT systems and platforms
• Managing change and adoption
• Measuring governance effectiveness

Data Governance & Information Lifecycle Management Capstone Workshop and Best Practices
• Analyzing a data governance scenario
• Defining governance roles and lifecycle controls
• Identifying gaps and improvement actions
• Final review and best practices

• Data Governance Fundamentals & Governance Architecture
• Data Classification, Metadata & Quality Management
• Retention Policies, Access Control & Compliance Frameworks
• Lifecycle Management, Archiving & Information Stewardship
• Testing, Debugging & Governance Optimization
• End-to-End Data Governance Implementation Project

Participants will be evaluated through scenario-based discussions, data governance design exercises, and interactive workshops conducted during the training. The evaluation focuses on understanding governance concepts, lifecycle management practices, and the ability to apply them to real-world organizational data scenarios.

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Upon successful completion of the training, participants will receive the AcadNXT Certification for Data Governance & Information Lifecycle Management. This certification validates the learner’s foundational knowledge of data governance frameworks, lifecycle controls, accountability models, and best practices for managing enterprise data assets.