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Within the methodology, the implementation of best practices is defined. Data Vault 2.0 has a focus on including new components such as big data, NoSQL - and also focuses on the performance of the existing model. The old specification (documented here for the most part) is highly focused on data vault modeling.
A common data model (CDM) can refer to any standardised data model which allows for data and information exchange between different applications and data sources.Common data models aim to standardise logical infrastructure so that related applications can "operate on and share the same data", [1] and can be seen as a way to "organize data from many sources that are in different formats into a ...
This runtime data model transformation adds processing overhead and complicates the design of service compositions. [5] In order to avoid the need for data model transformation, the Canonical Schema pattern dictates the use of standardized data models for those business documents that are commonly processed by the services in a service inventory.
A canonical model is a design pattern used to communicate between different data formats. Essentially: create a data model which is a superset of all the others ("canonical"), and create a "translator" module or layer to/from which all existing modules exchange data with other modules. The canonical model acts as a middleman.
A Canonical XML document is by definition an XML document that is in XML Canonical form, defined by The Canonical XML specification. Briefly, canonicalization removes whitespace within tags, uses particular character encodings, sorts namespace references and eliminates redundant ones, removes XML and DOCTYPE declarations, and transforms ...
The tokenization system must be secured and validated using security best practices [6] applicable to sensitive data protection, secure storage, audit, authentication and authorization. The tokenization system provides data processing applications with the authority and interfaces to request tokens, or detokenize back to sensitive data.
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (Meta)data use vocabularies that follow FAIR principles I3.
A best current practice, abbreviated as BCP, [1] is a de facto level of performance in engineering and information technology. It is more flexible than a standard , since techniques and tools are continually evolving.