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| Section | Objectives |
|---|
| Data Management Fundamentals | - Content and Document Management
- 1. Records management
- 2. Unstructured data management
- 3. Content lifecycle management
- Data Quality
- 1. Data profiling and cleansing
- 2. Data quality dimensions
- 3. Data quality measurement and improvement
- Data Governance
- 1. Governance bodies and organizational roles
- 2. Policies, standards, and procedures
- 3. Governance framework and scope
- 4. Data quality management
- Data Warehousing and Business Intelligence
- 1. Reporting and visualization
- 2. Data warehousing concepts and architectures
- 3. BI and analytics fundamentals
- Data Storage and Operations
- 1. Data storage design principles
- 2. Database architecture and technology
- 3. Database security and access control
- Data Architecture
- 1. Architecture frameworks and tools
- 2. Enterprise data architecture concepts
- 3. Data modeling and design
- Master Data and Reference Data
- 1. Reference data management
- 2. Master data management processes
- 3. MDM and RDM concepts
- Data Integration and Interoperability
- 1. Data interoperability standards
- 2. Data integration techniques
- 3. ETL/ELT processes
- Data Ethics
- 1. Privacy and consumer protection
- 2. Ethical principles and practices
- 3. Responsible AI and algorithmic bias
- Data Security
- 1. Privacy regulations compliance
- 2. Data classification and handling
- 3. Security frameworks and controls
- Data Strategy
- 1. Strategic planning process
- 2. Data management strategy development
- 3. Data governance strategy
- Data Modeling and Design
- 1. Conceptual, logical, and physical models
- 2. Data modeling techniques
- 3. Normalization and denormalization
- Data Risk Management
- 1. Risk mitigation strategies
- 2. Data protection and compliance
- 3. Risk identification and assessment
- Data Business and Data Management
- 1. Data management frameworks
- 2. Data management definitions and principles
- 3. Business drivers and data roles
- Metadata Management
- 1. Metadata standards and integration
- 2. Metadata architecture and repository
- 3. Metadata types and definitions
|
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DAMA Data Management Fundamentals Sample Questions (Q33-Q38):
NEW QUESTION # 33
Governance ensures data is managed, but is not include the actual act of managing data.
Answer: B
NEW QUESTION # 34
Several global regulations have significant implications on data management practices. Examples include:
- A. Privacy laws
- B. BCBS 239
- C. PCI-DSS
- D. SPCA
- E. Effectiveness of education Standards
- F. Data Standards
Answer: A,B,C
NEW QUESTION # 35
An enterprise's organisation chart has multiple levels, each with a single reporting line. This is an example of a:
- A. Ecological taxonomy
- B. Hybrid taxonomy
- C. Hierarchical taxonomy
- D. Flat taxonomy
- E. Compound taxonomy
Answer: C
NEW QUESTION # 36
In a SQL injection attack, a perpetrator inserts authorized database statements into a vulnerable SQL data channel, such as a stored procedure.
Answer: A
NEW QUESTION # 37
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
Answer: B
NEW QUESTION # 38
......
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