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DAMA DMF-1220 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Management Fundamentals- Data Business and Data Management
  • 1. Data management frameworks
  • 2. Business drivers and data roles
  • 3. Data management definitions and principles
- Content and Document Management
  • 1. Unstructured data management
  • 2. Records management
  • 3. Content lifecycle management
- Data Modeling and Design
  • 1. Data modeling techniques
  • 2. Normalization and denormalization
  • 3. Conceptual, logical, and physical models
- Data Governance
  • 1. Governance framework and scope
  • 2. Policies, standards, and procedures
  • 3. Data quality management
  • 4. Governance bodies and organizational roles
- Data Quality
  • 1. Data quality dimensions
  • 2. Data quality measurement and improvement
  • 3. Data profiling and cleansing
- Data Strategy
  • 1. Data management strategy development
  • 2. Data governance strategy
  • 3. Strategic planning process
- Data Storage and Operations
  • 1. Data storage design principles
  • 2. Database security and access control
  • 3. Database architecture and technology
- Data Ethics
  • 1. Privacy and consumer protection
  • 2. Ethical principles and practices
  • 3. Responsible AI and algorithmic bias
- Data Warehousing and Business Intelligence
  • 1. Data warehousing concepts and architectures
  • 2. BI and analytics fundamentals
  • 3. Reporting and visualization
- Master Data and Reference Data
  • 1. Reference data management
  • 2. Master data management processes
  • 3. MDM and RDM concepts
- Data Risk Management
  • 1. Data protection and compliance
  • 2. Risk mitigation strategies
  • 3. Risk identification and assessment
- Data Integration and Interoperability
  • 1. Data interoperability standards
  • 2. ETL/ELT processes
  • 3. Data integration techniques
- Data Architecture
  • 1. Architecture frameworks and tools
  • 2. Data modeling and design
  • 3. Enterprise data architecture concepts
- Metadata Management
  • 1. Metadata standards and integration
  • 2. Metadata architecture and repository
  • 3. Metadata types and definitions
- Data Security
  • 1. Data classification and handling
  • 2. Privacy regulations compliance
  • 3. Security frameworks and controls

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DAMA Data Management Fundamentals Sample Questions (Q503-Q508):

NEW QUESTION # 503
Data quality issues only emerge at initial stages of the data lifecycle.

Answer: B


NEW QUESTION # 504
Corporate Information Factory (CIF) components include:

Answer: D,E,F


NEW QUESTION # 505
Big data management requires:

Answer: C

Explanation:
Big data management involves handling large, complex, and unstructured datasets, requiring greater discipline in governance, quality, and processing compared to relational data. The DAMA-DMBOK states:
"Big data management requires more discipline than traditional relational data management due to the volume, velocity, variety, and veracity challenges" (DMBOK2, Chapter 13: Data Integration and Interoperability, p. 521).
Options A, B, D, and E are incorrect: big data requires discipline, not less or none, and budgets or certifications are irrelevant to the question.
Reference:DAMA-DMBOK2, Chapter 13: Data Integration and Interoperability, Section 4.3, p. 521.


NEW QUESTION # 506
Data handling ethics are concerned with how to procure, store, manage, use and dispose of data in ways that are aligned with ethical principles.

Answer: A


NEW QUESTION # 507
How can the Data Governance process in an organisation best support the requirements of various Regulatory reporting needs?

Answer: D


NEW QUESTION # 508
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