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Course Outline
INTRODUCTION TO DAMA
- Definition of data management and its critical importance.
- Overview of the distinct disciplines within data management.
- DAMA and the DMBoK 2.0, along with their relationship to other frameworks (such as TOGAF/COBIT…).
- Survey of available professional certifications with a focus on the DAMA CDMP.
DATA GOVERNANCE
- Definition of Data Governance and its importance, including a typical data governance reference model.
- Primary data governance roles: owner, steward, and custodian.
- The function of the Data Governance Office (DGO) and its interaction with the PMO.
- Distinctions between Data Governance and IT Governance, and why these differences matter.
- Overview of data management implications related to selected regulations.
- Key steps organizations can take to prepare for compliance with current and future regulations.
- Strategies for initiating, sustaining, and building data governance capabilities.
DATA LIFECYCLE MANAGEMENT
- Proactive planning for managing data throughout its lifecycle.
- Distinctions between the data lifecycle and the Systems Development Lifecycle (SDLC).
- Integration of data governance touchpoints across the data lifecycle.
METADATA MANAGEMENT
- Definition of metadata and its significance.
- Types of metadata, their applications, and sources.
- The connection between metadata and business glossaries.
- How metadata serves as the essential link for data governance and metadata standards.
DG MINI PROJECT
- Launching the Data Governance Program: essential early requirements and developing a realistic business case for DG aligned with business objectives.
DOCUMENT RECORDS & CONTENT MANAGEMENT
- The importance of document and records management.
- Differences between taxonomy and ontology.
- Legal and regulatory factors affecting records and content management.
DATA MODELING BASICS
- Types of data models, their uses, and interrelationships.
- Development and utilization of data models, spanning from enterprise and conceptual levels to logical, physical, and dimensional models.
- Maturity assessment to evaluate how models are used in the enterprise and integrated into the System Development Life Cycle (SDLC).
- Data modeling in the context of big data.
- The critical role of data modeling in data governance, supported by a business case study.
DATA QUALITY MANAGEMENT
- The various facets of data quality and why validity is often mistaken for quality.
- Policies, procedures, metrics, technology, and resources necessary to ensure data quality.
- A data quality reference model and its practical application.
- The interconnection between data quality management and data governance, illustrated with case studies.
DATA OPERATIONS MANAGEMENT
- Core roles and considerations for 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 personal data abuse.
- Identifying risks to data and its usage beyond just security concerns.
- Data management considerations for various regulations, such as GDPR and BCBS239.
- The role of data governance in managing data security.
MASTER & REFERENCE DATA MANAGEMENT
- Differences between reference and master data.
- Identification and management of master data across the enterprise.
- Four generic MDM architectures and their suitability for different scenarios.
- Incremental implementation of MDM to align with business priorities.
- Case study of Statoil (Equinor).
DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
- Definition of data warehousing and business intelligence, and the necessity for these systems.
- Major data warehouse architectures (Inmon & Kimball).
- Introduction to dimensional data modeling.
- Reasons why master data management often fails without adequate data governance.
- Data analytics, machine learning, and data visualization.
DATA INTEGRATION & INTEROPERABILITY
- Business and technological issues that data integration aims to resolve.
- Differences between data integration and data interoperability.
- Various styles of data integration and interoperability, their applicability, and implications.
- Approaches and guidelines for providing data integration and access.
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
