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Pass Your DMF-1220 Dumps as PDF Updated on 2026 With 725 Questions

DAMA DMF-1220 Real Exam Questions and Answers FREE

DAMA DMF-1220 Exam Syllabus Topics:

Section Objectives
Topic 1: Data Management Fundamentals – Data Storage and Operations

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

– Data Quality

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

– Data Governance

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

– Data Business and Data Management

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

– Data Architecture

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

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

– Master Data and Reference Data

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

– Data Ethics

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

– Data Strategy

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

– Data Risk Management

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

– Metadata Management

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

– Data Integration and Interoperability

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

– Content and Document Management

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

– Data Security

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

 

QUESTION 274
Data models are critical to effective management of data. They:

 
 
 
 
 
 

QUESTION 275
What is the final step in the development of a business-data-driven roadmap?

 
 
 
 
 

QUESTION 276
Data flows map and document relationships between data and locations where global differences occur.

 
 

QUESTION 277
Do experts feel a Data Lake needs data management?

 
 
 
 
 

QUESTION 278
What position is responsible for the quality and use of their organization’s data assets?

 
 
 
 
 

QUESTION 279
A data warehouse deployment with multiple ETL, storage and querying tools often suffers due to the lack of:

 
 
 
 
 

QUESTION 280
Risk classifications describe the sensitivity of the data and the likelihood that it might be sought after for malicious purposes.

 
 

QUESTION 281
In an information management context, the short-term wins and goals often arise from the resolution of an identified problem.

 
 

QUESTION 282
Subtype absorption: The subtype entity attributes are included as nullable columns into a table representing the supertype entity

 
 

QUESTION 283
Data Management and Data Governance Maturity models require planning before implementation. Planning is important because:

 
 
 
 
 

QUESTION 284
A control activity in the metadata management environment includes loading statistical analysis.

 
 

QUESTION 285
Consistent input data reduces the chance of errors in associating records. Preparation processes include:

 
 
 

QUESTION 286
The load step of ETL is physically storing or presenting the results of the transformation in the target system.

 
 

QUESTION 287
Development of goals, principles and policies derived from the data governance strategy will not guide the organization into the desired future state.

 
 

QUESTION 288
Examples of interaction models include:

 
 
 
 

QUESTION 289
The deliverables in the data architecture context diagram include:

 
 
 
 
 
 

QUESTION 290
Deliverables in the data quality context diagram include:

 
 
 
 
 
 

QUESTION 291
Enterprise data architecture description must include both [1] as well as [2]

 
 
 
 

QUESTION 292
Examples of data enhancement includes:

 
 
 
 
 
 

QUESTION 293
All DMM and Data Governance assessments should identify its objectives and goals for improvement. This is important because:

 
 
 
 
 

QUESTION 294
Data profiling is a form of data analysis used to inspect data and assess quality.

 
 

QUESTION 295
When data is classified as either security data or regulatory data, the result will be:

 
 
 
 
 

QUESTION 296
SOA stands for:

 
 
 
 

QUESTION 297
Elements that point to differences between warehouses and operational systems include:

 
 
 
 
 
 

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