"The former is a political concept and forms part of international relations and Internet governance."
This is the set of policies, procedures, and standards that organizations use to ensure data is accurate, secure, and meets regulatory requirements.
Introduction to Data Governance: A basic understanding of what Data Governance is, its importance, and its benefits for businesses.
Data Governance Framework: A structured approach to defining, designing, and implementing a Data Governance program that aligns with business goals.
Governance Policies and Procedures: Establishing policies and procedures to ensure that data is managed, maintained, and shared appropriately across the organization.
Data Quality Management: Techniques for ensuring the accuracy, completeness, and consistency of data across all systems and processes.
Data Classification and Security: Developing an understanding of the types of data that an organization holds and how to protect it from unauthorized access.
Data Privacy and Compliance: Understanding the regulations and norms that govern data privacy, such as GDPR or HIPAA, and how to implement them.
Data Ownership and Stewardship: Identifying key data custodians within your organization, defining their responsibilities and accountabilities, and establishing a system for data stewardship.
Data Management and Architecture: Designing and implementing an effective data management strategy that aligns with business objectives, and ensuring that architecture supports data management goals.
Metadata Management: The process of identifying, creating, and managing metadata that helps to understand, connect, and analyze data.
Data Governance Best Practices: Establishing key performance indicators (KPIs) and metrics to measure the success of your Data Governance program.
Change Management: Ensuring that the Data Governance program is flexible enough to evolve with the changing business environment and emerging technologies.
Education and Communication: Educating stakeholders on the importance of Data Governance, and communicating progress and results to the broader organization.
Compliance Governance: This refers to the rules and regulations set forth governing data usage, handling, protection and retention.
Privacy Governance: This involves the control of sensitive and personal data, to ensure it is not exploited, mishandled, or misused.
Security Governance: This type of data governance focuses on the implementation and enforcement of policies designed to protect data's confidentiality, integrity and availability.
Operational Governance: This covers the end-to-end management of data operations, workflows and processes with the aim of ensuring that data is driving business value.
Regulatory Governance: This category includes oversight and validation of regulations to ensure compliance with industry standards and government laws.
Metadata Governance: This ensures that the data is correctly tagged and can be efficiently identified.
Master Data Management Governance: This concerns the governance of enterprise-wide data assets.
Quality Governance: This type of governance focuses on ensuring accurate data, whether it be the input, output or transformation of data, and aligns all data with data standards.
Information Lifecycle Management Governance: Data governance that oversees the whole data lifecycle, from creation through disposal.
Enterprise Information Management Governance: It is the term given to coordinated, all-encompassing management of an organization's data and information assets.
IT Governance: This includes policies, strategies and practices for IT within an organization.
Data Steward Governance: The roles and responsibilities of data stewards are defined in this framework, which has the goal of data stewardship.
Business Analytics Governance: It comprises data warehouse management and the governance of business intelligence.
Metadata Management Governance: This aims to organize metadata from various sources, such as databases, spreadsheets, and cloud storage, ensuring that all information is consistent, accurate, and easily accessible.
Data Classification Governance: It classifies data by security, sensitivity, and risk level, to ensure adequate safeguards and protections are established.
"The latter is a data management concept and forms part of corporate data governance."