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For instance, when customer data are duplicated and attached with each product bought, then redundancy of data is a known source of inconsistency since a given customer might appear with different values for one or more of their attributes. [4]
Database normalization is the process of structuring a relational database 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 .
The importance of point-in-time consistency can be illustrated with what would happen if a backup were made without it. Assume Wikipedia's database is a huge file, which has an important index located 20% of the way through, and saves article data at the 75% mark. Consider a scenario where an editor comes and creates a new article at the same time a backup is being performed, which is being ...
The CAP theorem is based on three trade-offs, one of which is "atomic consistency" (shortened to "consistency" for the acronym), about which the authors note, "Discussing atomic consistency is somewhat different than talking about an ACID database, as database consistency refers to transactions, while atomic consistency refers only to a property of a single request/response operation sequence.
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...
proceed with the operation and thus provide availability but risk inconsistency. Note this doesn't necessarily mean that system is highly available to its users. [5] CAP theorem Euler diagram. Thus, if there is a network partition, one has to choose between consistency or availability.
Although DBMSs have greatly improved the shareability of data, the use of a DBMS alone does not guarantee a consistent definition of data. Furthermore, most large companies have had to develop multiple databases which are often under the control of different DBMSs and still have the problems of redundancy and inconsistency. [6]
Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").