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Data quality control is the process of controlling the usage of data for an application or a process. This process is performed both before and after a Data Quality ...
ISO 8000 is the international standard for Data Quality and Enterprise Master Data.Widely adopted internationally [1] [2] [3] it describes the features and defines the requirements for standard exchange of Master Data among business partners.
[5] notes that "Thus far, none of those [25] significant institutions – some of which are classified as global systemically important banks – have fully implemented the BCBS 239 principles", adding that "Weaknesses stem mainly from a lack of clarity regarding responsibility and accountability for data quality". The report concludes, amongst ...
In fact, a considerable amount of information quality research involves investigating and describing various categories of desirable attributes (or dimensions) of data. Research has recently shown the huge diversity of terms and classification structures used.
Within systems engineering, quality attributes are realized non-functional requirements used to evaluate the performance of a system. These are sometimes named architecture characteristics, or "ilities" after the suffix many of the words share.
Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. [1] Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. [2]
Quality of Data (QoD) is a designation coined by L. Veiga, that specifies and describes the required Quality of Service of a distributed storage system from the Consistency point of view of its data. It can be used to support big data management frameworks, Workflow management, and HPC systems (mainly for data replication and consistency).
The new specification consists of three pillars: methodology (SEI/CMMI, Six Sigma, SDLC, etc..), the architecture (amongst others an input layer (data stage, called persistent staging area in Data Vault 2.0) and a presentation layer (data mart), and handling of data quality services and master data services), and the model. Within the ...