DAMA DMF-1220 Practice Test Questions Answers
Exam Code: DMF-1220
(Updated 582 Q&As)
Exam Name: Data Management Fundamentals
Last Update: 23-Mar-2025
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DMF-1220 Overview
DAMA DMF-1220 Exam Overview
| Aspect | Details |
|---|---|
| Exam Name | DAMA DMF-1220 – Certified Data Management Professional (CDMP) Exam |
| Certification | CDMP (Certified Data Management Professional) |
| Duration | 2.5 hours (150 minutes) |
| Number of Questions | Approximately 100 questions |
| Exam Format | Multiple choice questions (MCQs), scenario-based questions |
| Passing Score | 70% or higher |
| Language | English |
| Exam Mode | Online or In-Person Proctored |
| Prerequisites | 1. Basic knowledge of data management concepts 2. Experience in data management and governance |
| Topics Covered | 1. Data Governance 2. Data Architecture 3. Data Quality Management 4. Data Modeling 5. Metadata Management 6. Data Integration 7. Data Warehousing 8. Master Data Management (MDM) |
| Preparation Resources | 1. DAMA DMBoK (Data Management Body of Knowledge) 2. CDMP study guides and practice exams 3. DAMA webinars and courses |
| Tools & Technologies Covered | Concepts and practices applicable to most data management tools (e.g., data modeling, ETL, MDM, metadata management) |
| Recommended Experience | 2-5 years of experience working in data management or related fields |
| Topics Breakdown (Approx. %) | - Data Governance: 15-20% - Data Architecture: 15-20% - Data Quality Management: 15-20% - Data Modeling: 15-20% - Metadata Management: 10-15% - Data Integration: 10-15% - Master Data Management: 5-10% |
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DAMA DMF-1220 Exam Topics Breakdown
| Exam Section | Topics Covered | Approx. Percentage |
|---|---|---|
| 1. Data Governance | - Principles of data governance - Policies, standards, and procedures - Compliance and regulatory frameworks |
15-20% |
| 2. Data Architecture | - Data modeling techniques - Data design and integration architectures - Database design and management |
15-20% |
| 3. Data Quality Management | - Data quality frameworks - Techniques for data profiling, cleansing, and validation - Measuring and improving data quality |
15-20% |
| 4. Data Modeling | - Logical and physical data models - Data model types (conceptual, relational, dimensional, etc.) - Normalization and denormalization |
15-20% |
| 5. Metadata Management | - Metadata management practices - Data lineage and data cataloging - Tools and techniques for managing metadata |
10-15% |
| 6. Data Integration | - Data integration techniques - ETL and ELT processes - Data pipelines and workflow management |
10-15% |
| 7. Master Data Management (MDM) | - MDM concepts and frameworks - Managing data across multiple systems - Data stewardship and governance for MDM |
5-10% |
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