E-commerce Dictionary

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

The legal principle that digital data is subject to the laws and governance of the country in which it is physically collected, stored, or processed.

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.

Data virtualization is a technology that integrates data from disparate sources into a single, virtual view without physically moving or copying the data.

Data import is the process of bringing data from an external source into a target system. In e-commerce, this often involves populating a PIM with product information from various sources like ERPs or supplier feeds.

Data integrity ensures data is accurate, consistent, and reliable throughout its lifecycle. It is crucial for making informed decisions and maintaining customer trust in e-commerce operations.

Data manipulation is the process of transforming raw data into a structured, clean, and usable format for various applications. It involves cleaning, validating, enriching, and organizing data to meet specific requirements.

Data normalization is the process of structuring data to reduce redundancy and improve data integrity, often involving standardizing formats and values.

Data validation is the process of ensuring that data entered or processed in a system is accurate, consistent, and adheres to predefined rules and formats.

A centralized system designed to aggregate, manage, and distribute all product data specifically for e-commerce operations.