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Sunday, March 28, 2010

Calidad de Sistemas y Datos

Data quality 
Data are of high quality "if they are fit for their intended uses in operations, decision making and planning" (J. M. Juran). Alternatively, the data are deemed of high quality if they correctly represent the real-world construct to which they refer. Furthermore, apart from these definitions, as data volume increases, the question of internal consistency within data becomes paramount, regardless of fitness for use for any external purpose, e.g. a person's age and birth date may conflict within different parts of a database. The first views can often be in disagreement, even about the same set of data used for the same purpose. This article discusses the concept as it related to business data processing, although of course other data have various quality issues as well.
Contents

List of system quality attributes














Many of these quality attributes can also be applied to data quality. 
Common subsets
  • A subset of them (Reliability, Availability, Serviceability, Usability, and Installability) are together referred to as RASUI.
  • Another subset used for Software Requirements (Functionality, Usability, Reliability, Performance, Supportability) are together referred to as FURPS.
  • For databases RASR is an important concept (Reliability, Availability, Scalability, and Recoverability).
  • When dealing with safety-critical systems, the acronym RAMS (Reliability, Availability, Maintainability and Safety) is frequently used.
  • For interoperable software a common subset is (Portability, Operability, Openness and Predictability), sometimes referred to as POOP.
Information quality

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