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MongoDB can be used as a file system, called GridFS, with load-balancing and data-replication features over multiple machines for storing files. This function, called a grid file system, [36] is included with MongoDB drivers. MongoDB exposes functions for file manipulation and content to developers.
As each query result and each proxy object is a view to the underlying data, any change made to the database is reflected in all objects that point to the same data. Realm generally calls this behavior "zero-copy architecture" (along with the previously mentioned lazy-loaded data access).
A key aspect of specification by example is creating a single source of truth about required changes from all perspectives. When business analysts work on their own documents, software developers maintain their own documentation and testers maintain a separate set of functional tests, software delivery effectiveness is significantly reduced by the need to constantly coordinate and synchronise ...
The Data-driven design describes structures that reside within the software. Attributes and relationships between data objects dictate the choice of data structures. The architecture design uses information flowing characteristics, and maps them into the program structure. The transformation mapping method is applied to exhibit distinct ...
The Case Report Tabulation Data Definition Specification (define.xml) draft version 2.0, the oldest data definition specification, is part of the evolution from the 1999 FDA electronic submission (eSub) guidance and electronic Common Technical Document (eCTD) documents specifying that a document describing the content and structure of included ...
Crosswalk tables are often employed within or in parallel to enterprise systems, especially when multiple systems are interfaced or when the system includes legacy system data. In the context of Interfaces, they function as an internal extract, transform, load (ETL) mechanism. For example, this is a metadata crosswalk from MARC standards to ...
Yet another example of grouping the data is the use of some commonly used numerical values, which are in fact "names" we assign to the categories. For example, let us look at the age distribution of the students in a class. The students may be 10 years old, 11 years old or 12 years old. These are the age groups, 10, 11, and 12.
A good example of metadata is the cataloging system found in libraries, which records for example the author, title, subject, and location on the shelf of a resource. Another is software system knowledge extraction of software objects such as data flows, control flows, call maps, architectures, business rules, business terms, and database schemas.