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A process image is a copy of a given process's state at a given point in time. It is often used to create persistence within an otherwise volatile system. A common example is a database management system (DBMS). Most DBMS can store the state of its database or databases to a file before being closed down (see database dump). The DBMS can then ...
For example, backing up a single database to 4 tape drives at once. Normal backup. full backup used by Windows Server 2003. Near store. provisionally backing up data to a local staging backup device, possibly for later archival backup to a remote store device. Open file backup. the ability to back up a file while it is in use by another ...
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.
Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1] A database management system manages the data accordingly.
A backup strategy requires an information repository, "a secondary storage space for data" [7] that aggregates backups of data "sources". The repository could be as simple as a list of all backup media (DVDs, etc.) and the dates produced, or could include a computerized index, catalog, or relational database.
The name is commonly used when creating a query to the database. The Database Source Name (DSN) does not have to be the same as the filename for the database. For example, a database file named "friends.mdb" could be set up with a DSN of "school". Then DSN "school" would then be used to refer to the database when performing a query.
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Another advantage of the functional model is that it is a database with features such as data independence, concurrent multiuser access, integrity, scalability, security, audit trail, backup/recovery, and data integration. Data independence is of particularly high value for analytics. Data need no longer reside in spreadsheets.