Terminology
2225 terms, tools, patterns and metrics an architect is expected to use precisely. Each one gets a short explanation of what it is, and — where it matters — what it is commonly confused with. Search filters as you type; the column headers sort.
All areas2225
Architecture Fundamentals77
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Data Governance & Semantics74
Frontend & Experience Architecture66
Edge, Mobile & IoT68
Regulatory & Data Protection Architecture65
Assurance, Audit & Model Risk69
6 terms shown.
| Term | Kind | Topic | What it is |
|---|---|---|---|
| Classification Propagation Label Inheritance, Lineage-Aware Classification, Derived Sensitivity | practice | Sensitivity Labelling | Carrying a column's sensitivity classification through every derived table, view and export, so that copying restricted data into an aggregate does not silently strip its protection. |
| Classification Propagation Labels Travelling Through Lineage, Derived-Data Sensitivity | practice | Sensitivity Labelling | Carrying a sensitivity label through every derivation, so a restricted column copied into an aggregate, a training set or an export remains subject to its controls. |
| Label Inheritance Classification Propagation, Sensitivity Inheritance | practice | Sensitivity Labelling | Automatically assigning a derived dataset the highest sensitivity of its inputs, so that aggregates and transformations do not silently escape the controls that applied to their sources. |
| Over-Classification Label Inflation, Maximum Propagation Collapse | concept | Sensitivity Labelling | The state in which so much of an estate carries the highest sensitivity label that its controls become unworkable, and people route around them - producing less protection than a coarser scheme would. |
| Sensitivity Labelling Data Classification Tagging | practice | Sensitivity Labelling | Attaching a machine-readable classification to data at the column or asset level, so that downstream controls can be applied automatically. |
| Sensitivity Propagation | concept | Sensitivity Labelling | The rule that a derived dataset inherits the highest sensitivity of its inputs unless a named transformation demonstrably lowers it. |
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