Glossary D
Glossary D
Deutsch: Schaden / Español: Daño / Português: Dano / Français: Dommage / Italiano: Danno
Damage in the context of quality management refers to the deterioration or loss of value of a product, service, or brand, which can affect its intended function, performance, or perception among stakeholders. This concept is pivotal as it directly impacts customer satisfaction, brand reputation, and the financial health of an organization.
Deutsch: Gefahr / Español: Peligro / Português: Perigo / Français: Danger / Italiano: Pericolo
Danger in the context of quality management refers to potential sources of harm, risk, or adverse outcomes that may affect processes, products, services, or stakeholders. It encompasses situations or factors that threaten the achievement of quality objectives, compliance with standards, or the safety of end-users, employees, or the environment.
Deutsch: Datenungenauigkeit / Español: Inexactitud de datos / Português: Inexactidão de dados / Français: Inexactitude des données / Italiano: Inaccuratezza dei dati
Data Inaccuracy refers to errors or discrepancies in data that affect its Reliability, Precision, or validity. In the context of quality management, data inaccuracy can undermine decision-making processes, lead to faulty analysis, and negatively impact overall operational efficiency. Accurate data is critical for ensuring quality standards, as it drives process improvements, compliance, and customer satisfaction.
Deutsch: Datensicherheit / Español: Integridad de los datos / Português: Integridade dos dados / Français: Intégrité des données / Italiano: Integrità dei dati
In the realm of quality management, ensuring the accuracy and consistency of data is paramount. This concept is encapsulated by the term data integrity, which refers to the maintenance of data accuracy and consistency over its entire life cycle. It is a critical aspect of data management that safeguards against corruption, loss, or unauthorized access, thereby upholding the reliability of information systems.
Deutsch: Dateninterpretation / Español: Interpretación de datos / Português: Interpretação de dados / Français: Interprétation des données / Italiano: Interpretazione dei dati
Data interpretation in the quality management context refers to the process of analysing, understanding, and drawing meaningful conclusions from data generated through various quality management processes. This includes evaluating data collected from production, inspections, audits, and customer feedback to assess product quality, identify trends, and make informed decisions for continuous improvement. Effective data interpretation helps organisations monitor performance, identify defects, control variability, and ensure compliance with quality standards.
Deutsch: Datenmanagement / Español: Gestión de datos / Português: Gestão de dados / Français: Gestion des données / Italian: Gestione dei dati
Data Management in the context of quality management refers to the systematic handling of data, including its collection, storage, processing, analysis, and security, to ensure its accuracy, reliability, and availability. In quality management, data management is critical for making informed decisions, maintaining compliance with standards, and driving continuous improvement in processes and products.
Deutsch: Datenmatrix / Español: Matriz de datos / Português: Matriz de dados / Français: Matrice de données / Italiano: Matrice dei dati
Data Matrix is a two-dimensional barcode that encodes information in a compact, machine-readable format. In the context of quality management, Data Matrix codes are used to track and trace products, components, and materials throughout the production and supply chain processes. They play a crucial role in ensuring product quality, authenticity, and compliance with regulatory standards.
Deutsch: Datensicherheit / Español: Seguridad de datos / Português: Segurança de dados / Français: Sécurité des données / Italiano: Sicurezza dei dati
The protection of sensitive information within quality management systems is a critical component for ensuring compliance, reliability, and trust. Data Security refers to the measures and protocols implemented to safeguard digital data from unauthorized access, corruption, or theft throughout its lifecycle. In the context of quality management, it ensures that product specifications, audit records, and process documentation remain intact and confidential.