E-commerce Dictionary

Data governance establishes policies and processes to manage data availability, usability, integrity, and security across an organization.

Data ingestion is the process of collecting, importing, and processing raw data from various sources into a system like a PIM, often involving initial validation and transformation.

A centralized repository for storing large volumes of raw, unstructured, and semi-structured product data from various sources before it's processed or structured.

Data lineage tracks the origin, transformations, and destinations of data, providing a complete audit trail for compliance, quality, and understanding data flows.

Specific instructions defining how data fields from a source system correspond to fields in a target system, ensuring accurate data transfer and transformation.

A data model defines the structure, relationships, and constraints of data within a system, organizing how product information is stored and managed.

Data Quality Monitoring is the continuous process of tracking, measuring, and reporting on the quality of data over time. It identifies inconsistencies, errors, and gaps to ensure data remains accurate and reliable.

A software component that defines, applies, and enforces data quality rules to ensure product information meets predefined standards.

A data quality score is a quantifiable metric that assesses the completeness, accuracy, consistency, and timeliness of a dataset or specific data points.

An individual or team responsible for the quality, integrity, and governance of specific data domains within an organization.

Data stewardship involves the responsibility for managing, overseeing, and ensuring the quality and integrity of an organization's data assets.

Data transformation is the process of converting data from one format or structure into another, often necessary for data integration and syndication.