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An application may be made up of many different types of data, various types of files and data feeds from other applications. Application consistency is the state in which all related files and databases are synchronized representing the true status of the application.
In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints , cascades , triggers , and any combination thereof.
The application should specify the consistency requirements that satisfy the application semantics. In this model, an application specifies each consistency requirement as a conit (abbreviation of consistency units). A conit can be a physical or logical consistency and is used to measure the consistency.
Atomicity, consistency, isolation (sometimes integrity), durability is a transaction metric. When dealing with safety-critical systems, the acronym reliability, availability, maintainability and safety is frequently used. [citation needed] Dependability is an aggregate of availability, reliability, safety, integrity and maintainability.
Eventual consistency is a weak guarantee – most stronger models, like linearizability, are trivially eventually consistent. Eventually-consistent services are often classified as providing BASE semantics (basically-available, soft-state, eventual consistency), in contrast to traditional ACID (atomicity, consistency, isolation, durability).
Phrased otherwise, unbiasedness is not a requirement for consistency, so biased estimators and tests may be used in practice with the expectation that the outcomes are reliable, especially when the sample size is large (recall the definition of consistency). In contrast, an estimator or test which is not consistent may be difficult to justify ...
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...
"the usefulness, accuracy, and correctness of data for its application" [10] Arguably, in all these cases, "data quality" is a comparison of the actual state of a particular set of data to a desired state, with the desired state being typically referred to as "fit for use," "to specification," "meeting consumer expectations," "free of defect ...