Pdf DAMA DMF-1220 Version | DMF-1220 Practice Exam Questions

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DAMA DMF-1220 Exam Syllabus Topics:

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

Section

Objectives

Topic 1: Data Management Fundamentals

- Data Security

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

- Data Strategy

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

- Content and Document Management

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

- Data Warehousing and Business Intelligence

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

- Data Quality

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

- Data Integration and Interoperability

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

- Data Risk Management

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

- Data Storage and Operations

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

- Data Ethics

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

- Master Data and Reference Data

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

- Data Business and Data Management

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

- Data Governance

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

- Data Modeling and Design

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

- Metadata Management

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

- Data Architecture

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

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DAMA Data Management Fundamentals Sample Questions (Q368-Q373):

NEW QUESTION # 368
Repositories facilitate the collection, publishing and distribution of data in a centralized and possibly standardized way. Data is most often used to:

A. Find new initiatives for the business to pursue
B. Give developers all the data they will need for programming
C. Make sure the DBAs are not creating new tables and columns
D. Document and organize the provided data
E. To support the business users not the technical users

Answer: D

NEW QUESTION # 369
Control activities to manage metadata stores include:

A. Load statistical analysis
B. Missing metadata reports
C. Job scheduling and monitoring
D. Definitions resolutions improvement
E. Roadmap extrapolation
F. Lineage

Answer: A,B,C

NEW QUESTION # 370
Which of the following are must-do for any successful Data Governance programme?

A. Create a training programme for all for data owners and data stewards.
B. Set up a wiki for incorrect data definitions.
C. Allocate Data Ownership responsibilities according to their role in the organization.
D. Create a communications plan to inform to all stakeholders what you are doing.
E. Ensure there is a Data Governance Policy with which everyone in the organization is required to comply.

Answer: E

NEW QUESTION # 371
A catastrophic system failure due to processing attachments that are too large may be solved by:

A. Increasing the available memory on the database
B. Compressing the attachment before sending it in an email
C. Changing the network bandwidth to handle infinitely sized attachments
D. Associating attachment date with the attachment and changing the process tocheck the date is less than 1 month old
E. Associating attachment size with the attachment and changing the process to check the size is less than the upper limit

Answer: E

NEW QUESTION # 372
The best preventative action to prevent poor quality data from entering an organisation include:

A. Implement data governance and stewardship
B. None of the above
C. Train data procedures
D. Define and enforce rules
E. Institute a formal change control
F. Establish data entry controls

Answer: A,C,D,E,F

NEW QUESTION # 373
......

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