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Course Outline
INTRODUCTION TO DAMA
- Defining data management and its critical importance.
- Identifying the various disciplines within data management.
- DAMA & the DMBoK 2.0, and its alignment with other frameworks (such as TOGAF/COBIT).
- An overview of professional certifications, with a focus on the DAMA CDMP.
DATA GOVERNANCE
- Understanding Data Governance, its importance, and a typical reference model.
- Key data governance roles: owner, steward, and custodian.
- The function of the Data Governance Office (DGO) and its relationship with the PMO.
- Distinguishing between Data Governance and IT Governance, and understanding why it matters.
- Overview of data management implications for selected regulations.
- Essential steps organizations should take to prepare for compliance with current and future regulations.
- Strategies for initiating, sustaining, and building effective data governance.
DATA LIFECYCLE MANAGEMENT
- Proactive planning for managing data across its entire lifecycle.
- Distinguishing between the data lifecycle and the Systems Development Lifecycle (SDLC).
- Identifying data governance touch points throughout the data lifecycle.
METADATA MANAGEMENT
- Defining metadata and explaining its importance.
- Types of metadata, their uses, 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 elements and how to develop a realistic business case aligned with business 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 usage, and interrelationships.
- Developing and leveraging data models, spanning from enterprise-level and conceptual to logical, physical, and dimensional models.
- Conducting maturity assessments to evaluate how models are utilized within 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, featuring a business case study.
DATA QUALITY MANAGEMENT
- Exploring the facets of data quality and clarifying why validity is often mistaken for quality.
- The policies, procedures, metrics, technology, and resources required to ensure data quality.
- A data quality reference model and its practical application.
- The interconnection between data quality management and data governance, supported by case studies.
DATA OPERATIONS MANAGEMENT
- Core roles and considerations for data operations.
- Best practices for data operations.
DATA RISK & SECURITY
- Identifying threats and adopting defenses to prevent unauthorized access, use, or loss of data, particularly the abuse of personal data.
- Identifying risks (beyond just security) to 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 data and master data.
- Identifying and managing master data across the enterprise.
- Four generic MDM architectures and their suitability for different scenarios.
- Incremental implementation of MDM to align with business priorities.
- Statoil (Equinor) case study.
DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
- Defining data warehousing and business intelligence, and the necessity for both.
- Major data warehouse architectures (Inmon & Kimball).
- Introduction to dimensional data modeling.
- Understanding why master data management fails without adequate data governance.
- Data analytics, machine learning, and data visualization.
DATA INTEGRATION & INTEROPERABILITY
- Addressing the business and technology issues that data integration seeks to resolve.
- Distinguishing between data integration and data interoperability.
- Different 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
