Data Management Practice Exam
Data Management Practice Exam
About Data Management Exam
The Data Management Certification Exam is a comprehensive assessment designed to evaluate a candidate’s knowledge and practical understanding of managing data as a strategic asset within an organization. With data playing a critical role in digital transformation, analytics, compliance, and operational efficiency, this certification equips professionals with the frameworks, methodologies, and best practices needed to govern, secure, store, and utilize data effectively across various enterprise environments. The exam validates a well-rounded proficiency in core areas such as data governance, data architecture, metadata management, data quality, master data management (MDM), data lifecycle management, and regulatory compliance. Successfully achieving this certification signals readiness to contribute to organizational data strategy and governance efforts with confidence and precision.
Who should take the Exam?
This certification is ideal for:
- Data managers, data stewards, and data architects seeking formal recognition of their competencies
- Database administrators and IT professionals responsible for handling organizational data assets
- Business intelligence and analytics professionals who rely on structured, high-quality data
- Compliance and risk management personnel needing to align data practices with regulatory requirements
- Consultants and project managers working in data-intensive projects or digital transformation initiatives
- Aspiring professionals and students looking to enter the data governance or data management field
- CIOs and CDOs (Chief Data Officers) aiming to implement enterprise data strategies and frameworks
Skills Required
To successfully attempt the exam, candidates should have or be prepared to acquire the following competencies:
- Understanding of data governance principles and data stewardship roles
- Familiarity with data architecture design and enterprise data modeling
- Knowledge of data lifecycle management from creation to archival and deletion
- Proficiency in data quality assessment and improvement techniques
- Hands-on experience with metadata management tools and techniques
- Working knowledge of relational databases and data warehousing concepts
- Familiarity with regulatory frameworks such as GDPR, HIPAA, or CCPA
- Conceptual understanding of MDM, data integration, and ETL processes
Knowledge Gained
Upon completion of this certification, candidates will:
- Understand the principles of data management and governance at an enterprise level
- Be able to define, organize, and implement data management strategies and policies
- Gain expertise in data modeling, data architecture, and system interoperability
- Learn how to assess and manage data quality across departments
- Develop capabilities to manage metadata and enable data lineage tracking
- Know how to implement and sustain a master data management system
- Understand how to align data practices with compliance and privacy standards
- Be able to facilitate cross-functional collaboration through effective data stewardship
Course Outline
Domain 1 - Introduction to Data Management
- Definition and importance of data as an enterprise asset
- Data management lifecycle and its alignment with business strategy
- Industry standards and frameworks (DAMA-DMBOK, ISO 8000, DCAM)
Domain 2 - Data Governance and Stewardship
- Building a data governance framework
- Roles and responsibilities of data stewards
- Policies, standards, and data ethics
Domain 3 - Data Architecture and Modeling
- Logical vs. physical data models
- Enterprise data architecture design
- Normalization, schema design, and reference architecture
Domain 4 - Metadata Management
- Types of metadata and their applications
- Metadata repositories and tools
- Enabling data lineage and discoverability
Domain 5 - Data Quality Management
- Dimensions of data quality (accuracy, completeness, consistency)
- Root cause analysis and data cleansing techniques
- Implementing data quality metrics and dashboards
Domain 6 - Master Data Management (MDM)
- MDM principles and components
- Hub-and-spoke vs. registry models
- Data matching, deduplication, and hierarchy management
Domain 7 - Data Storage, Security, and Lifecycle
- Data classification and lifecycle stages
- Backup, archiving, and retention policies
- Data privacy, encryption, and access controls
Domain 8 - Data Integration and Interoperability
- ETL, ELT, and real-time data pipelines
- APIs, middleware, and enterprise data buses
- Ensuring system interoperability across platforms
Domain 9 - Regulatory Compliance and Risk Management
- Overview of global data protection laws (GDPR, HIPAA, etc.)
- Data risk identification and mitigation
- Preparing for audits and maintaining compliance
