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DAMA DMF-1220 Exam Syllabus Topics:

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

Section

Objectives

Topic 1: Data Management Fundamentals

- Data Quality

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

- Data Storage and Operations

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

- Data Modeling and Design

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

- Data Strategy

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

- Data Architecture

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

- Data Business and Data Management

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

- Data Risk Management

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

- Master Data and Reference Data

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

- Data Warehousing and Business Intelligence

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

- Data Ethics

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

- Content and Document Management

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

- Metadata Management

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

- Data Governance

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

- Data Security

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

- Data Integration and Interoperability

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

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DAMA Data Management Fundamentals Sample Questions (Q24-Q29):

NEW QUESTION # 24
Poorly managed Metadata leads to, among other, redundant data and data management processes.

A. FALSE
B. TRUE

Answer: B

NEW QUESTION # 25
Which Data Architecture artefact contains the names of key business entities, their relationships, critical guiding business rules and critical attributes?

A. Enterprise Business Glossary
B. Enterprise Data Model
C. Enterprise Semantic Model
D. Enterprise Data Standards
E. Enterprise Data Flows

Answer: B

NEW QUESTION # 26
ISO 8000 will describe the structure and the organization of data quality management, including:

A. Data Quality Planning
B. Data Quality Availability
C. Data Quality Assurance
D. Data Quality Improvement
E. Data Quality Control

Answer: A,C,D,E

NEW QUESTION # 27
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.

A. FALSE
B. TRUE

Answer: B

NEW QUESTION # 28
What key components must be included in the Implementation Roadmap?

A. Timeframes and resources for policies and directives Architecture, Tools and Control Metrics
B. Testing requirements, risk assessment, data security and privacy policies and database design
C. Data metrics, physical data structures, and data model designs
D. Timeframes and resources for Policies and Directives, a Business Glossary Architecture, Business and IT processes and role descriptions
E. Timeframes and resources for data quality requirements, policies and directives and testing standards

Answer: D

NEW QUESTION # 29
......

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