
Cleansing is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in data to ensure its accuracy and reliability for data processing and analytics.
Cleansing is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in data to ensure its accuracy and reliability for data processing and analytics.
Domain Ownership is the practice of having clear accountability and responsibility for a specific domain of data within an organization’s data infrastructure.
Data Validation Rules is a set of predefined criteria used to verify the accuracy, completeness, and consistency of data.
Quality Assessment is the process of evaluating the accuracy, completeness, reliability, and consistency of data, ensuring its fitness for specific purposes.
Metadata Management is the process of organizing and managing information about data assets, including their attributes, relationships, and governance policies, to enable effective data processing and analytics.
Master Data Management is a process that ensures consistent and accurate data across an organization’s different systems and applications.
Lineage Tracking is a method for tracking and documenting the origin and transformation history of data.
Data Stewardship is the practice of managing and maintaining high-quality data to ensure its accuracy, consistency, and availability for processing and analysis.
Data Standardization is the process of transforming data into a consistent and uniform format for improved data processing and analytics.
Data Remediation is the process of identifying, correcting, and removing errors or inconsistencies in data to ensure its quality and reliability for processing and analysis.
Data Provenance is the record-keeping of the origin, movement, and transformation of data throughout its lifecycle, providing visibility and traceability.
Data Profiling is a process that analyzes data to gain insights into its structure, quality, and content, aiding in data processing and analytics.
Data Ownership is the responsibility and control over data that an organization has, ensuring data quality, security, and compliance.
Data Dictionary is a centralized repository of metadata that provides a comprehensive and organized view of the data within an organization.
Data Custodianship is the process of managing and protecting data assets within an organization, ensuring data quality, security, and compliance.