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Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
An industry standard data model, or simply standard data model, is a data model that is widely used in a particular industry. The use of standard data models makes the exchange of information easier and faster because it allows heterogeneous organizations to share an agreed vocabulary, semantics, format, and quality standard for data.
This database acts as a data warehouse for the organization and also stores information regarding the relationships among its assets. [2] The CMDB provides a means of understanding the organization's critical assets and their relationships, such as information systems , upstream sources or dependencies of assets, and the downstream targets of ...
These sites contain documents and links about the different Web services standards identified on this page. IBM Developerworks: Standard and Web Service [2] innoQ's WS-Standard Overview ("Diagram" (PDF).) MSDN .NET Developer Centre: Web Service Specification Index Page; OASIS Standards and Other Approved Work
In computing, Open Database Connectivity (ODBC) is a standard application programming interface (API) for accessing database management systems (DBMS). The designers of ODBC aimed to make it independent of database systems and operating systems .
A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider.
One of its goals is to reduce the need for data transformations as two services interact with each other, which can be achieved if the service contracts use standardized data models e.g. XML schemas if the services have been implemented as web services. This also helps in making services more interoperable.
Distributed computing system middleware can loosely be divided into two categories—those that provide human-time services (such as web request servicing) and those that perform in machine-time. This latter middleware is somewhat standardized through the Service Availability Forum [ 9 ] and is commonly used in complex, embedded systems within ...