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Course Outline
INTRODUCTION TO DAMA
- An overview of data management and its critical importance.
- The various disciplines within the field of data management.
- The role of DAMA and the DMBoK 2.0, and how they relate to other frameworks such as TOGAF and COBIT.
- An overview of professional certifications available in data management, with a focus on the DAMA CDMP certification.
DATA GOVERNANCE
- Understanding Data Governance and its significance. Introduction to a typical data governance reference model.
- Key roles in data governance, including owner, steward, and custodian.
- The function of the Data Governance Office (DGO) and its relationship with the Project Management Office (PMO).
- Differentiating between Data Governance and IT Governance, and the implications of this distinction.
- Implications of various regulations on data management practices.
- Steps organizations can take to prepare for compliance with current and future regulations.
- Strategies for initiating, sustaining, and building a robust data governance program.
DATA LIFECYCLE MANAGEMENT
- Proactive strategies for managing data throughout its lifecycle.
- Comparing the data lifecycle with the Systems Development Lifecycle (SDLC).
- Key touchpoints for data governance within the data lifecycle.
METADATA MANAGEMENT
- The definition and importance of metadata.
- Types of metadata, their uses, and sources.
- The relationship between metadata and business glossaries.
- How metadata serves as a critical component in data governance and the establishment of metadata standards.
DG MINI PROJECT
- Initiating a Data Governance Program: Essential early steps. Strategies for developing a realistic business case for Data Governance that aligns with organizational objectives.
DOCUMENT RECORDS & CONTENT MANAGEMENT
- The importance of document and records management.
- Differentiating between taxonomy and ontology.
- Legal and regulatory considerations affecting records and content management.
DATA MODELING BASICS
- Types of data models, their applications, and how they interrelate.
- The development and utilization of data models, from enterprise to conceptual, logical, physical, and dimensional levels.
- Assessing the maturity of data modeling practices within an organization and their integration into the System Development Lifecycle (SDLC).
- Data modeling in the context of big data.
- The critical role of data modeling in data governance, illustrated by a BP case study.
DATA QUALITY MANAGEMENT
- The various aspects of data quality and the common confusion between validity and quality.
- Policies, procedures, metrics, technology, and resources for ensuring high data quality.
- A reference model for data quality management and its practical application.
- The interconnection between data quality management and data governance, supported by case studies.
DATA OPERATIONS MANAGEMENT
- Core roles and considerations in data operations.
- Best practices for effective data operations.
DATA RISK & SECURITY
- Identifying threats and implementing defenses to prevent unauthorized access, use, or loss of data, particularly in the context of personal data abuse.
- Recognizing risks beyond security that impact data and its usage.
- Data management considerations for various regulations, such as GDPR and BCBS239.
- The role of data governance in managing data security.
MASTER & REFERENCE DATA MANAGEMENT
- Distinguishing between reference and master data.
- Strategies for identifying and managing master data across the enterprise.
- Four generic MDM architectures and their suitability in different scenarios.
- Incremental approaches to implementing MDM that align with business priorities.
- A case study from Statoil (Equinor).
DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
- An introduction to data warehousing and business intelligence, and their importance.
- Major data warehouse architectures, including Inmon and Kimball models.
- Fundamentals of dimensional data modeling.
- The necessity of adequate data governance for successful master data management.
- Data analytics, machine learning, and data visualization techniques.
DATA INTEGRATION & INTEROPERABILITY
- Business and technological challenges that data integration seeks to address.
- Distinguishing between data integration and data interoperability.
- Various styles of data integration and interoperability, their applicability, and implications.
- Guidelines and approaches for providing data integration and access solutions for government.
35 Hours
Testimonials (7)
Very engaging
Samieg - Vodacom
Course - Certified Data Management Professional (CDMP)
it was very interactive and although I was not exposed to some modules before, Gaurav made it easy to understand. Good Participation in the team
UVASH - Vodacom
Course - Certified Data Management Professional (CDMP)
The training covered all the areas that were required. Very Insightful.
Carol - Vodacom
Course - Certified Data Management Professional (CDMP)
Material was covered according to the weight of the exam's marks. gave a better understanding of this course. Quizes helped a lot
Saika - Vodacom
Course - Certified Data Management Professional (CDMP)
Quizzes to test our knowledge and white board work kept us engaged.
Paula Dunsby - Vodacom
Course - Certified Data Management Professional (CDMP)
The instructor was very simple and clear on the point of the course
Mohamed - Dubai Government Human Resources Department - DGHR
Course - Certified Data Management Professional (CDMP)
Practical knowledge of the trainer
