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DAMA DMF-1220 Exam Syllabus Topics:

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

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DAMA Data Management Fundamentals Sample Questions (Q546-Q551):

NEW QUESTION # 546
Data quality management is a key capability of a data management practice and organization.

Answer: B


NEW QUESTION # 547
In the context of big data the Three V's refer to: Volume, Velocity and Validity

Answer: A


NEW QUESTION # 548
With reliable Metadata an organization does not know what data it has, what the data represents and how it moves through the systems, who has access to it, or what it means for the data to be of high quality.

Answer: A


NEW QUESTION # 549
Which of the following is a stage in the Shewhart / Deming Cycle that drives the data quality improvement lifecycle?

Answer: D

Explanation:
The correct answer is E. The Shewhart/Deming improvement cycle is the Plan-Do-Check-Act (PDCA) cycle, a continuous improvement model widely applied to quality management. During Plan , the organization identifies the problem or improvement opportunity and determines an appropriate course of action. During Do , the proposed change is implemented or tested. Check evaluates the resulting data and determines whether the change achieved the intended improvement, while Act standardizes successful changes or initiates another improvement cycle. Of the choices presented, only "Do" is an actual PDCA stage.
Investigate, Correct, Rerun, and Perform may describe activities occurring during improvement work, but they are not formal stages of the Shewhart/Deming cycle. ASQ likewise defines the Deming/Shewhart cycle as Plan, Do, Check, and Act.


NEW QUESTION # 550
A node is a group of computers hosting either processing or data as part of a distributed database.

Answer: A


NEW QUESTION # 551
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