Data anonymization is transforming data so that individuals cannot reasonably be identified from it, even when it is combined with other available information. Teams use it to share health or customer records with researchers, or to build realistic test datasets, without exposing personal details.
Data privacy is the set of practices and controls governing how personal data is collected, used, shared, stored and deleted. It follows the law and what people were told.
Encryption at rest and in transit means protecting data with encryption both while it is stored and while it moves across networks. Stolen or intercepted data then stays unreadable without the keys.
The GDPR (General Data Protection Regulation) is the EU law governing how organisations collect, use, store and share personal data about people in the EU. It sets duties for businesses and gives individuals enforceable rights.
Training data is the set of examples a machine learning model learns from. Its quality, coverage and labelling largely determine how well the model performs.
Data residency is the requirement or decision to store and process data in a specific country or region. It is driven by law, regulation, contracts or customer expectations, and shapes how cloud and AI systems are deployed.
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