Data Governance Implementation
Expert-defined terms from the Professional Certificate in Data Governance course at London School of Planning and Management. Free to read, free to share, paired with a professional course.
Acquisition refers to the process of obtaining data from various sources, which… #
It involves collecting, processing, and storing data in a manner that ensures its quality, security, and compliance with regulatory requirements. Related terms include data collection, data processing, and data storage. Acquisition is essential in data governance as it lays the foundation for subsequent data management activities.
Accuracy is a measure of how close a value is to the true value, and it is a cri… #
It refers to the degree to which data is free from errors, inconsistencies, and inaccuracies. Related terms include precision, recall, and F1 score. Ensuring accuracy is vital in data governance as it directly impacts the reliability and trustworthiness of data-driven decisions.
Access control refers to the mechanisms and policies that regulate who can acces… #
It involves implementing measures such as authentication, authorization, and encryption to protect data from unauthorized access or malicious activities. Related terms include authentication, authorization, and encryption. Access control is essential in data governance as it ensures the confidentiality, integrity, and availability of data.
Audit refers to the process of examining and evaluating an organization's data m… #
It involves assessing the effectiveness of data governance policies, procedures, and controls to ensure compliance with regulatory requirements and industry standards. Related terms include compliance, risk assessment, and internal control. Audits are essential in data governance as they help identify areas for improvement and ensure that data management practices are aligned with organizational objectives.
Authentication refers to the process of verifying the identity of users, systems… #
It involves using mechanisms such as passwords, biometrics, or tokens to ensure that only authorized entities can access data or systems. Related terms include authorization, encryption, and identity management. Authentication is essential in data governance as it ensures the security and integrity of data.
Authorization refers to the process of granting or denying access to data or sys… #
It involves using mechanisms such as access control lists, group policies, or role-based access control to regulate data access. Related terms include authentication, encryption, and identity management. Authorization is essential in data governance as it ensures that data is accessed and used in accordance with organizational policies and regulatory requirements.
Availability refers to the degree to which data is accessible and usable when ne… #
It involves ensuring that data is properly stored, processed, and retrieved to meet business requirements. Related terms include data backup, data recovery, and system downtime. Ensuring availability is vital in data governance as it directly impacts the efficiency and effectiveness of business operations.
Backup refers to the process of creating copies of data to prevent loss or corru… #
It involves using mechanisms such as backup software, storage devices, or cloud services to create and store data backups. Related terms include data recovery, disaster recovery, and business continuity. Backup is essential in data governance as it ensures the continuity of business operations in the event of data loss or disruption.
Cloud computing refers to the delivery of computing resources and services over… #
It involves using cloud-based infrastructure, platforms, or applications to store, process, and manage data. Related terms include cloud storage, cloud security, and cloud governance. Cloud computing is essential in data governance as it provides scalability, flexibility, and cost-effectiveness in data management.
Compliance refers to the adherence to regulatory requirements, industry standard… #
It involves ensuring that data management practices are aligned with relevant laws, regulations, and standards to avoid legal, financial, or reputational risks. Related terms include regulatory requirements, industry standards, and organizational policies. Compliance is essential in data governance as it ensures the integrity and trustworthiness of data-driven decisions.
Data architecture refers to the design and structure of an organization's data a… #
It involves creating a framework that defines how data is collected, stored, processed, and used to support business operations. Related terms include data modeling, data warehousing, and data integration. Data architecture is essential in data governance as it provides a foundation for effective data management and decision-making.
Data asset refers to any collection of data that has value to an organization, w… #
It involves identifying, categorizing, and managing data assets to ensure their quality, security, and compliance with regulatory requirements. Related terms include data classification, data categorization, and data valuation. Data assets are essential in data governance as they provide a foundation for data-driven decision-making and business operations.
Data backup refers to the process of creating copies of data to prevent loss or… #
Data backup is essential in data governance as it ensures the continuity of business operations in the event of data loss or disruption.
Data classification refers to the process of categorizing data based on its sens… #
It involves using mechanisms such as data labeling, data tagging, or data categorization to ensure that data is handled and protected accordingly. Related terms include data protection, data security, and data privacy. Data classification is essential in data governance as it ensures that data is managed and protected in accordance with its value and risk.
Data discovery refers to the process of identifying, locating, and retrieving da… #
It involves using mechanisms such as data search, data indexing, or data analytics to discover and extract data. Related terms include data exploration, data mining, and data visualization. Data discovery is essential in data governance as it enables organizations to identify and leverage data assets to support business operations.
Data encryption refers to the process of converting data into a coded form to pr… #
It involves using mechanisms such as encryption algorithms, encryption keys, or encryption protocols to ensure the confidentiality and integrity of data. Data encryption is essential in data governance as it ensures the security and trustworthiness of data.
Data governance refers to the overall management and oversight of an organizatio… #
It involves creating policies, procedures, and controls to ensure the quality, security, and compliance of data with regulatory requirements. Related terms include data management, data quality, and data security. Data governance is essential as it provides a framework for effective data management and decision-making.
Data integration refers to the process of combining data from multiple sources t… #
It involves using mechanisms such as data warehousing, data virtualization, or data federation to integrate data. Related terms include data consolidation, data aggregation, and data transformation. Data integration is essential in data governance as it enables organizations to create a single, unified view of their data assets.
Data management refers to the overall process of planning, organizing, and contr… #
Related terms include data governance, data quality, and data security. Data management is essential as it provides a framework for effective data management and decision-making.
Data masking refers to the process of hiding or obscuring sensitive data to prot… #
It involves using mechanisms such as data encryption, data tokenization, or data anonymization to ensure the confidentiality and integrity of data. Data masking is essential in data governance as it ensures the security and trustworthiness of data.
Data mining refers to the process of discovering patterns, relationships, and in… #
It involves using mechanisms such as data analytics, data visualization, or data machine learning to extract insights from data. Related terms include data exploration, data discovery, and data science. Data mining is essential in data governance as it enables organizations to identify and leverage data assets to support business operations.
Data modeling refers to the process of creating a conceptual representation of a… #
It involves using mechanisms such as data entity relationship diagrams, data flow diagrams, or data object models to create a framework for data management. Related terms include data architecture, data design, and data development. Data modeling is essential in data governance as it provides a foundation for effective data management and decision-making.
Data privacy refers to the protection of personal or sensitive data from unautho… #
It involves using mechanisms such as data encryption, data anonymization, or data pseudonymization to ensure the confidentiality and integrity of data. Related terms include data protection, data security, and data compliance. Data privacy is essential in data governance as it ensures the trustworthiness and security of data.
Data protection refers to the measures taken to prevent data loss, corruption, o… #
It involves using mechanisms such as data backup, data recovery, or data encryption to ensure the confidentiality, integrity, and availability of data. Related terms include data security, data privacy, and data compliance. Data protection is essential in data governance as it ensures the security and trustworthiness of data.
Data quality refers to the degree to which data is accurate, complete, and consi… #
It involves using mechanisms such as data validation, data verification, or data certification to ensure the quality of data. Related terms include data accuracy, data completeness, and data consistency. Data quality is essential in data governance as it directly impacts the reliability and trustworthiness of data-driven decisions.
Data recovery refers to the process of restoring data from backups or other sour… #
It involves using mechanisms such as data backup, data replication, or data archiving to ensure the availability and integrity of data. Related terms include data backup, disaster recovery, and business continuity. Data recovery is essential in data governance as it ensures the continuity of business operations in the event of data loss or disruption.
Data security refers to the measures taken to protect data from unauthorized acc… #
It involves using mechanisms such as data encryption, data access control, or data authentication to ensure the confidentiality, integrity, and availability of data. Related terms include data protection, data privacy, and data compliance. Data security is essential in data governance as it ensures the security and trustworthiness of data.
Data storage refers to the mechanisms and technologies used to store and manage… #
It involves using mechanisms such as data warehousing, data lakes, or data cloud storage to store and manage data. Related terms include data management, data governance, and data quality. Data storage is essential in data governance as it provides a foundation for effective data management and decision-making.
Data validation refers to the process of checking data for accuracy, completenes… #
It involves using mechanisms such as data verification, data certification, or data validation rules to ensure the quality of data. Data validation is essential in data governance as it directly impacts the reliability and trustworthiness of data-driven decisions.
Data visualization refers to the process of presenting data in a graphical or vi… #
It involves using mechanisms such as data charts, data graphs, or data maps to communicate insights and trends. Related terms include data analytics, data mining, and data science. Data visualization is essential in data governance as it enables organizations to identify and leverage data assets to support business operations.
Data warehousing refers to the process of creating a centralized repository of d… #
It involves using mechanisms such as data integration, data aggregation, or data transformation to create a unified view of data. Data warehousing is essential in data governance as it provides a foundation for effective data management and decision-making.
Disaster recovery refers to the process of restoring business operations in the… #
It involves using mechanisms such as data backup, data recovery, or data replication to ensure the availability and integrity of data. Related terms include business continuity, disaster recovery plan, and emergency response. Disaster recovery is essential in data governance as it ensures the continuity of business operations in the event of a disaster or major disruption.
Encryption refers to the process of converting data into a coded form to protect… #
Encryption is essential in data governance as it ensures the security and trustworthiness of data.
Information lifecycle management refers to the process of managing the creation,… #
It involves using mechanisms such as information classification, information retention, or information disposal to ensure the quality, security, and compliance of information with regulatory requirements. Related terms include data management, data governance, and information security. Information lifecycle management is essential in data governance as it provides a framework for effective information management and decision-making.
Metadata refers to the information that describes, explains, or summarizes data,… #
It involves using mechanisms such as metadata creation, metadata management, or metadata repository to provide context and meaning to data. Related terms include data dictionary, data catalog, and data inventory. Metadata is essential in data governance as it enables organizations to understand and leverage their data assets.
Personal data refers to any information that can be used to identify, contact, o… #
It involves using mechanisms such as data protection, data security, or data anonymization to ensure the confidentiality and integrity of personal data. Related terms include personal identifiable information, sensitive data, and protected data. Personal data is essential in data governance as it requires special handling and protection to ensure the privacy and security of individuals.
Risk management refers to the process of identifying, assessing, and mitigating… #
It involves using mechanisms such as risk assessment, risk mitigation, or risk transfer to ensure the security and integrity of data. Related terms include risk analysis, risk evaluation, and risk monitoring. Risk management is essential in data governance as it enables organizations to identify and mitigate risks to their data assets.
Security refers to the measures taken to protect data from unauthorized access,… #
Security is essential in data governance as it ensures the security and trustworthiness of data.
Stewardship refers to the process of managing and overseeing an organization's d… #
It involves using mechanisms such as data governance, data management, or data quality to ensure the quality, security, and compliance of data with regulatory requirements. Related terms include data ownership, data accountability, and data responsibility. Stewardship is essential in data governance as it provides a framework for effective data management and decision-making.
Vendor management refers to the process of managing and overseeing an organizati… #
It involves using mechanisms such as vendor selection, vendor contracting, or vendor monitoring to ensure the quality, security, and compliance of vendor-provided data with regulatory requirements. Related terms include vendor risk management, vendor compliance, and vendor performance management. Vendor management is essential in data governance as it enables organizations to manage and mitigate risks associated with vendor-provided data.