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DAMA DMF-1220 Exam Syllabus Topics:

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

Section

Objectives

Data Management Fundamentals

- Data Security

1. Data classification and handling
2. Privacy regulations compliance
3. Security frameworks and controls

- Data Governance

1. Governance bodies and organizational roles
2. Policies, standards, and procedures
3. Governance framework and scope
4. Data quality management

- Data Ethics

1. Ethical principles and practices
2. Privacy and consumer protection
3. Responsible AI and algorithmic bias

- Content and Document Management

1. Content lifecycle management
2. Unstructured data management
3. Records management

- Data Strategy

1. Data governance strategy
2. Strategic planning process
3. Data management strategy development

- Data Modeling and Design

1. Conceptual, logical, and physical models
2. Data modeling techniques
3. Normalization and denormalization

- Data Business and Data Management

1. Business drivers and data roles
2. Data management frameworks
3. Data management definitions and principles

- Data Risk Management

1. Risk mitigation strategies
2. Risk identification and assessment
3. Data protection and compliance

- Data Integration and Interoperability

1. Data interoperability standards
2. ETL/ELT processes
3. Data integration techniques

- Master Data and Reference Data

1. MDM and RDM concepts
2. Reference data management
3. Master data management processes

- Data Quality

1. Data profiling and cleansing
2. Data quality measurement and improvement
3. Data quality dimensions

- Data Architecture

1. Data modeling and design
2. Architecture frameworks and tools
3. Enterprise data architecture concepts

- Data Storage and Operations

1. Database security and access control
2. Database architecture and technology
3. Data storage design principles

- Data Warehousing and Business Intelligence

1. Reporting and visualization
2. BI and analytics fundamentals
3. Data warehousing concepts and architectures

- Metadata Management

1. Metadata architecture and repository
2. Metadata types and definitions
3. Metadata standards and integration

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DAMA Data Management Fundamentals Sample Questions (Q668-Q673):

NEW QUESTION # 668
Obfuscating or redacting data is the practice of making information anonymous ot removing sensitive information. Risks are present in the following instances:

A. Data storage
B. Data marketing
C. Data marking
D. Data integration
E. Data masking
F. Data aggregation

Answer: C,E,F

NEW QUESTION # 669
Lack of automated monitoring represents serious risks, including:

A. Direction and recovery risk
B. Administrative and audit duties risk
C. Risk of reliance on inadequate native
D. Risk of compliance

Answer: A,B,C

NEW QUESTION # 670
Data modelling tools and model repositories are necessary for managing the enterprise data model in all levels.

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 671
Quality Assurance Testing (QA) is used to test functionality against requirements.

A. TRUE
B. FALSE

Answer: A

NEW QUESTION # 672
The business case for enterprise warehousing is:

A. To reduce data overload, improve information governance, and enable anenterprise to use its data to make better decisions
B. To increase data redundancy, align information glossaries, and enable anenterprise to exploit machine leaming techniques
C. To reduce data redundancy, improve information consistency, and enable anenterprise to use its data to make better decisions
D. To align data systems, improve source system management, and to enable anenterprise exploit machine learning techniques
E. To increase data distribution, improve information generation, and enable anenterprise to use its data to increase revenue

Answer: C

NEW QUESTION # 673
......

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