DAMA DG-1220: Data Governance Exam fundamentals
Data governance is the process of controlling and monitoring how data is created, managed, and used. Data governance is a combination of people, processes, and technology that provides for the effective and efficient management of an organization's data. The goal of data governance is to establish a transparent process for making decisions about the information that helps an organization achieve its strategic goals while maintaining compliance with regulations and laws.
Data governance can be thought of in three dimensions: structure, security, and usage. In order to ensure proper management of an organization's data assets, it's important to consider these three dimensions together. LatestCram DAMA DG-1220 exam dumps will help you to get certified and get highly paid job.
Structure refers to the way in which an organization defines its data assets-what types of data are generated by different departments or systems? How do these departments and systems interact with each other? How is this knowledge used within an organization? Security refers to who has access to what types of data, when they have access, how they use this information, etc. Usage refers to why people need access to certain types of data at certain times (i.e., what business reasons drive this need).
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DAMA DG-1220 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Governance Organization & Roles | 20% | - Governance council and steering committee - Decision rights and accountability - Data owner, data steward, data custodian - Operating models |
| Topic 2: Governance for Data Domains & Risk | 20% | - Governance for quality, metadata, security - Regulatory compliance (GDPR, CCPA, etc.) - Audit and assurance - Risk management and mitigation |
| Topic 3: Policies, Standards & Procedures | 20% | - Change management - Data policies and rules - Standards and guidelines - Issue management and escalation |
| Topic 4: Data Governance Concepts & Principles | 20% | - Ethics and compliance - Governance drivers and objectives - Data as an asset - Governance frameworks and models |
| Topic 5: Data Governance Implementation & Operations | 20% | - Metrics and KPIs - Communication and training - Governance roadmap and maturity - Monitoring and reporting |
