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Duration 35 hours
Course Outline
INTRODUCTION TO DAMA
- Definition of data management and its critical importance to organizational integrity.
- Identification of the various disciplines within data management frameworks.
- DAMA & the DMBoK 2.0, and its alignment with other established frameworks (TOGAF/COBIT…).
- Summary of available professional certifications, with a specific focus on DAMA CDMP.
DATA GOVERNANCE
- Definition of Data Governance and its strategic significance. Presentation of a standard data governance reference model.
- Key data governance roles: owner, steward, custodian.
- The function of the Data Governance Office (DGO) and its coordination with the PMO.
- Distinction between Data Governance and IT Governance, and the operational implications of this difference.
- Analysis of the Data Management implications of a selection of other regulations.
- Essential steps organizations should take to prepare for compliance with current and future regulations.
- Initiating data governance programs and strategies for sustaining and building data governance capabilities.
DATA LIFECYCLE MANAGEMENT
- Strategic planning for the management of data across its entire lifecycle.
- Distinctions between data life cycle and a Systems Development Lifecycle (SDLC).
- Data governance integration points throughout the data lifecycle.
METADATA MANAGEMENT
- Definition of metadata and the rationale for its importance.
- Classifications of metadata, their specific uses, and their sources.
- The relationship between metadata and business glossaries. Analysis of the connection.
- How metadata serves as the foundational link for data governance and metadata standards.
DG MINI PROJECT
- Initiating the Data Governance Program, identifying essential early implementations. Methodology for developing a realistic business case for DG linked to business objectives?
DOCUMENT RECORDS & CONTENT MANAGEMENT
- The strategic importance of document and records management.
- Taxonomy vs. ontology… analysis of the differences.
- Legal and regulatory considerations impacting records and content management.
DATA MODELING BASICS
- Classifications of data models, their operational use, and interrelationships.
- The development and utilization of data models, ranging from enterprise, through conceptual to logical, physical, and dimensional.
- Maturity assessment to evaluate how models are utilized in the enterprise and their integration in the System Development Life Cycle (SDLC).
- Data modeling applications in big data environments.
- Why data modeling plays a critical part in data governance and BP case study.
DATA QUALITY MANAGEMENT
- The various dimensions of data quality, and why validity is often confused with quality.
- The policies, procedures, metrics, technology, and resources required for ensuring data quality.
- A data quality reference model and methodology for its application.
- Why data quality management and data governance are interconnected and case studies.
DATA OPERATIONS MANAGEMENT
- Core roles and operational considerations for data operations.
- Best practices for effective data operations.
DATA RISK & SECURITY
- Identification of threats and the implementation of defenses to prevent unauthorized access, use, or loss of data, with particular emphasis on the protection of personal data.
- Identification of risks to data and its utilization, extending beyond security concerns.
- Data management considerations for different regulations, e.g. GDPR, BCBS239.
- The role of data governance in data security management.
MASTER & REFERENCE DATA MANAGEMENT
- Distinctions between reference and master data.
- Identification and management of master data across the enterprise.
- Four generic MDM architectures and their suitability for different operational scenarios.
- Strategies for incrementally implementing MDM to align with business priorities.
- Statoil (Equinor) case study.
DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
- Definition of data warehousing and business intelligence and the rationale for their necessity.
- The major data warehouse architectures (Inmon & Kimball).
- Introduction to dimensional data modeling.
- Why master data management fails without adequate data governance.
- Data analytics and machine learning and data visualization.
DATA INTEGRATION & INTEROPERABILITY
- Identification of the business (and technology) challenges that data integration seeks to resolve.
- Data integration and data interoperability - Analysis of the differences.
- Various models of data integration and interoperability, their applicability, and operational implications.
- The approaches and guidelines for provision of data integration and access.
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
