Data Governance ()
Description: The Data Governance Digital Business Capability refers to the ability of an organization to effectively manage and govern its data assets. It involves establishing policies, procedures, and frameworks to ensure data quality, integrity, security, and compliance. This capability enables organizations to have a holistic view of their data, make informed decisions based on reliable information, and ensure that data is used in a consistent and controlled manner across the enterprise. It also involves implementing data governance processes and tools to monitor and enforce data standards, resolve data-related issues, and enable data-driven decision-making at all levels of the organization. Additional information: The Data Governance Digital Business Capability refers to the ability of an organization to effectively manage and govern its data assets in a digital business environment. It encompasses the policies, processes, and practices that ensure the availability, integrity, confidentiality, and usability of data across the enterprise. Data governance involves establishing a framework that defines the roles, responsibilities, and decision-making processes related to data management. It aims to ensure that data is accurate, consistent, and reliable, and that it complies with relevant regulations and standards. The digital aspect of data governance emphasizes the need to manage data in the context of digital transformation initiatives and the increasing reliance on digital technologies. Key components of the Data Governance Digital Business Capability include: 1. Data Strategy: Developing a strategic plan that aligns data governance objectives with the overall business strategy. This involves defining the vision, goals, and objectives for data governance and identifying the key initiatives required to achieve them. 2. Data Policies and Standards: Establishing policies and standards that govern the collection, storage, processing, and sharing of data. These policies define data quality requirements, data classification and handling guidelines, data retention and disposal policies, and data privacy and security measures. 3. Data Stewardship: Assigning data stewards who are responsible for ensuring the quality, integrity, and compliance of data within their respective domains. Data stewards collaborate with data owners, users, and IT teams to define and enforce data standards, resolve data-related issues, and promote data governance best practices. 4. Data Quality Management: Implementing processes and tools to monitor, measure, and improve the quality of data. This includes data profiling, data cleansing, data validation, and data enrichment activities to ensure that data is accurate, complete, and consistent. 5. Data Privacy and Security: Establishing controls and measures to protect sensitive data from unauthorized access, disclosure, or misuse. This involves implementing data encryption, access controls, data masking, and data anonymization techniques to safeguard data privacy and comply with data protection regulations. 6. Data Lifecycle Management: Defining processes and procedures to manage the entire lifecycle of data, from creation to archival or disposal. This includes data capture, storage, integration, transformation, and archival strategies, as well as data backup and recovery mechanisms. 7. Data Governance Organization: Establishing a dedicated data governance team or committee responsible for overseeing and coordinating data governance activities. This team ensures that data governance policies and practices are effectively implemented, and it provides guidance and support to data stewards and other stakeholders. 8. Data Governance Tools and Technologies: Implementing data governance tools and technologies that facilitate data management, data quality monitoring, metadata management, and data lineage tracking. These tools enable automation, collaboration, and reporting capabilities to support efficient and effective data governance practices. By developing and maturing the Data Governance Digital Business Capability, organizations can ensure that their data assets are effectively managed, protected, and leveraged to drive business value, support decision-making processes, and enable digital transformation initiatives. Example: The Data Governance Digital Business Capability in the public sector refers to the ability to establish and enforce policies, procedures, and standards for managing data assets effectively. Here are some real examples of this capability in action: 1. Data Classification and Protection: Public sector organizations often deal with sensitive and confidential information. Data governance ensures that appropriate classification and protection mechanisms are in place to safeguard this data. For instance, a government agency may implement policies and procedures to classify data as public, internal, or confidential, and define access controls accordingly. 2. Data Quality Management: Public sector organizations rely on accurate and reliable data for decision-making and service delivery. Data governance enables the establishment of processes and controls to ensure data quality. For example, a municipality may implement data governance practices to regularly monitor and cleanse citizen data to maintain accurate records for service provision. 3. Data Sharing and Collaboration: Collaboration between different government agencies is crucial for effective governance and service delivery. Data governance facilitates the establishment of frameworks and agreements for sharing data securely and efficiently. For instance, a national healthcare system may implement data governance practices to enable secure sharing of patient information between hospitals and clinics to improve healthcare outcomes. 4. Compliance and Regulatory Reporting: Public sector organizations must adhere to various regulations and reporting requirements. Data governance ensures that data is managed in compliance with applicable laws and regulations. For example, a tax authority may implement data governance practices to ensure accurate and timely reporting of taxpayer information to meet regulatory obligations. 5. Data Privacy and Protection: Protecting citizens' privacy is a critical concern for public sector organizations. Data governance helps establish policies and controls to ensure compliance with privacy laws and protect personal information. For instance, a government agency may implement data governance practices to define procedures for handling and securing citizen data, ensuring compliance with data protection regulations. These examples demonstrate how the Data Governance Digital Business Capability in the public sector enables effective management, protection, and utilization of data assets to support governance, service delivery, compliance, and privacy requirements. Publisher: EIRA Team LOST view: OV-Data Spaces [Motivation] Identifier: http://data.europa.eu/dr8/egovera/DataGovernanceCapability EIRA traceability: eira:DigitalBusinessCapability EIRA concept: eira:SolutionBuildingBlock Last modification: 2023-07-10 dct:identifier: http://data.europa.eu/dr8/egovera/DataGovernanceCapability dct:title: Data Governance Digital Business Capability
eira:PURIhttp://data.europa.eu/dr8/egovera/DataGovernanceCapability
eira:ABBeira:DigitalBusinessCapability
dct:modified2023-07-10
dct:identifierhttp://data.europa.eu/dr8/egovera/DataGovernanceCapability
dct:titleData Governance Digital Business Capability
dct:descriptionThe Data Governance Digital Business Capability refers to the ability of an organization to effectively manage and govern its data assets. It involves establishing policies, procedures, and frameworks to ensure data quality, integrity, security, and compliance. This capability enables organizations to have a holistic view of their data, make informed decisions based on reliable information, and ensure that data is used in a consistent and controlled manner across the enterprise. It also involves implementing data governance processes and tools to monitor and enforce data standards, resolve data-related issues, and enable data-driven decision-making at all levels of the organization.
skos:exampleThe Data Governance Digital Business Capability in the public sector refers to the ability to establish and enforce policies, procedures, and standards for managing data assets effectively. Here are some real examples of this capability in action: 1. Data Classification and Protection: Public sector organizations often deal with sensitive and confidential information. Data governance ensures that appropriate classification and protection mechanisms are in place to safeguard this data. For instance, a government agency may implement policies and procedures to classify data as public, internal, or confidential, and define access controls accordingly. 2. Data Quality Management: Public sector organizations rely on accurate and reliable data for decision-making and service delivery. Data governance enables the establishment of processes and controls to ensure data quality. For example, a municipality may implement data governance practices to regularly monitor and cleanse citizen data to maintain accurate records for service provision. 3. Data Sharing and Collaboration: Collaboration between different government agencies is crucial for effective governance and service delivery. Data governance facilitates the establishment of frameworks and agreements for sharing data securely and efficiently. For instance, a national healthcare system may implement data governance practices to enable secure sharing of patient information between hospitals and clinics to improve healthcare outcomes. 4. Compliance and Regulatory Reporting: Public sector organizations must adhere to various regulations and reporting requirements. Data governance ensures that data is managed in compliance with applicable laws and regulations. For example, a tax authority may implement data governance practices to ensure accurate and timely reporting of taxpayer information to meet regulatory obligations. 5. Data Privacy and Protection: Protecting citizens' privacy is a critical concern for public sector organizations. Data governance helps establish policies and controls to ensure compliance with privacy laws and protect personal information. For instance, a government agency may implement data governance practices to define procedures for handling and securing citizen data, ensuring compliance with data protection regulations. These examples demonstrate how the Data Governance Digital Business Capability in the public sector enables effective management, protection, and utilization of data assets to support governance, service delivery, compliance, and privacy requirements.
eira:concepteira:SolutionBuildingBlock
skos:noteThe Data Governance Digital Business Capability refers to the ability of an organization to effectively manage and govern its data assets in a digital business environment. It encompasses the policies, processes, and practices that ensure the availability, integrity, confidentiality, and usability of data across the enterprise. Data governance involves establishing a framework that defines the roles, responsibilities, and decision-making processes related to data management. It aims to ensure that data is accurate, consistent, and reliable, and that it complies with relevant regulations and standards. The digital aspect of data governance emphasizes the need to manage data in the context of digital transformation initiatives and the increasing reliance on digital technologies. Key components of the Data Governance Digital Business Capability include: 1. Data Strategy: Developing a strategic plan that aligns data governance objectives with the overall business strategy. This involves defining the vision, goals, and objectives for data governance and identifying the key initiatives required to achieve them. 2. Data Policies and Standards: Establishing policies and standards that govern the collection, storage, processing, and sharing of data. These policies define data quality requirements, data classification and handling guidelines, data retention and disposal policies, and data privacy and security measures. 3. Data Stewardship: Assigning data stewards who are responsible for ensuring the quality, integrity, and compliance of data within their respective domains. Data stewards collaborate with data owners, users, and IT teams to define and enforce data standards, resolve data-related issues, and promote data governance best practices. 4. Data Quality Management: Implementing processes and tools to monitor, measure, and improve the quality of data. This includes data profiling, data cleansing, data validation, and data enrichment activities to ensure that data is accurate, complete, and consistent. 5. Data Privacy and Security: Establishing controls and measures to protect sensitive data from unauthorized access, disclosure, or misuse. This involves implementing data encryption, access controls, data masking, and data anonymization techniques to safeguard data privacy and comply with data protection regulations. 6. Data Lifecycle Management: Defining processes and procedures to manage the entire lifecycle of data, from creation to archival or disposal. This includes data capture, storage, integration, transformation, and archival strategies, as well as data backup and recovery mechanisms. 7. Data Governance Organization: Establishing a dedicated data governance team or committee responsible for overseeing and coordinating data governance activities. This team ensures that data governance policies and practices are effectively implemented, and it provides guidance and support to data stewards and other stakeholders. 8. Data Governance Tools and Technologies: Implementing data governance tools and technologies that facilitate data management, data quality monitoring, metadata management, and data lineage tracking. These tools enable automation, collaboration, and reporting capabilities to support efficient and effective data governance practices. By developing and maturing the Data Governance Digital Business Capability, organizations can ensure that their data assets are effectively managed, protected, and leveraged to drive business value, support decision-making processes, and enable digital transformation initiatives.
dct:publisherEIRA Team
dct:source
eira:viewOV-Data Spaces [Motivation]
eira:viewOV-Data Spaces
eira:viewOV-Digital Business Capabilities Catalogue