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Schema-agnosticism is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary. The increase in the size and in the semantic heterogeneity of database schemas bring new requirements for users querying and searching structured data. At this scale it can ...
Whenever the data can be treated as agnostic, the coding is simplified, as it only has to deal with one case (the data agnostic case) rather than multiple (PNG, PDF, etc.). When the data must be displayed or acted on, then it is interpreted based on the field definitions and formatting information, and returned to a data agnostic format as soon ...
Database abstraction layers reduce the amount of work by providing a consistent API to the developer and hide the database specifics behind this interface as much as possible. There exist many abstraction layers with different interfaces in numerous programming languages. If an application has such a layer built in, it is called database ...
A database management system (DBMS) is a computer program (or more typically, a suite of them) designed to manage a database, a large set of structured data, and run operations on the data requested by numerous users.
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
The technology plan is focused on the actual tangible elements to be used in the implementation of the data architecture design. Physical data architecture encompasses database architecture. Database architecture is a schema of the actual database technology that would support the designed data architecture.
When Vishakha Gupta and her co-founder Luis Remis were working together at Intel Labs in 2016, they were charged with figuring out how to manage growing amounts of visual data (images and video).
Metadata learning: SafePeak analyses the structure of the database schema, parses all types of schema objects (tables, views, triggers, functions, stored procedures, foreign keys) and creates an internal map of dependencies. On DDL commands, or schema changes, SafePeak automatically re-analyzes the modified objects and applies required changes ...