Data is one of the most valuable assets of an organization, but its value can only be realized when it is managed, protected, and governed effectively. This training provides a practical understanding of Data Management and Data Governance based on the DAMA-DMBOK (Data Management Body of Knowledge) framework, the globally recognized standard for data management best practices.
The program introduces participants to the core knowledge areas defined in DMBOK, including Data Governance, Data Architecture, Data Modeling and Design, Data Quality Management, Metadata Management, Master and Reference Data Management, Data Integration and Interoperability, Data Security, Data Warehousing and Business Intelligence, and Data Lifecycle Management. Participants will learn how these disciplines work together to ensure that data is accurate, trusted, secure, compliant, and aligned with business objectives.
Through practical examples, real-world case studies, and industry best practices, the training demonstrates how organizations can establish governance structures, define accountability for data assets, improve data quality, manage metadata and master data, comply with regulatory requirements, and create a strong foundation for analytics, digital transformation, and AI initiatives.
Participants will gain a holistic understanding of enterprise data management and learn how to implement governance practices that transform data into a strategic business asset, enabling better decision-making, operational efficiency, regulatory compliance, and sustainable business value.
Learning Objectives:
By the end of this course, participants will be able to:
- Understand the importance of data as an enterprise asset.
- Explain key concepts of Data Management and Data Governance.
- Identify governance structures, roles, and responsibilities.
- Apply data quality management principles and practices.
- Understand Metadata Management and Master Data Management (MDM).
- Manage data privacy, security, and regulatory compliance requirements.
- Understand data lifecycle management and stewardship practices.
- Establish policies, standards, and controls for trusted data.
- Measure and improve organizational data maturity.
- Enable analytics, AI, and business decision-making through governed data.
Upon completion, participants will understand how to apply DMBOK principles and practices to establish an enterprise-wide data management and governance capability that improves data trustworthiness, regulatory compliance, business agility, and AI readiness. Following modules will be covered in the training.
- Module 1: Introduction to Data Management and Governance
- Module 2: Data Lifecycle and Data Flow Fundamentals
- Module 3: Data Architecture and Data as a Product
- Module 4: Data Acquisition, Ingestion, Integration and Transformation
- Module 5: Data Governance Fundamentals
- Module 6: Data Quality Management
- Module 7: Metadata Management
- Module 8: Master and Reference Data Management (MDM/RDM)
- Module 9: Data Security, Privacy and Compliance
- Module 10: Data Governance for AI and Advanced Analytics
For more details please write to us at customer_relations@qaiglobal.com
Instructional Method
◆ Case studies and real-world scenarios
◆ Group discussions and collaborative exercises
◆ Simulations
◆ Self-assessment and reflection- Micro Quizzes
You will receive:
Certificate – QAI Training completion certificate for : Data Management and Data Governance Training.
Commercials (Excluding GST)
- Individual Registration: INR 12,000 per participant
- In-house Exclusive Batch (minimum 8 participants): INR 1,00,000. Additional Participants: INR 10,000 per person
The fees mentioned above are for virtual batches. For classroom sessions, pricing will vary based on location and logistics. Please contact us for a customized quote.
