Data Redundancy
Data redundancy occurs in database systems which have a
field that is repeated in two or more tables. For instance, in case when
customer data is duplicated and attached with each product bought then
redundancy of data is a known source of inconsistency, since customer might
appear with different values for given attribute.
Data redundancy means data anomalies and corruption and
generally should be avoided by design. Database normalization prevents redundancy
and makes the best possible usage of storage.
Proper use of foreign keys can minimize data redundancy
and chance of destructive anomalies. However sometimes concerns of efficiency
and convenience can result redundant data design despite the risk of corrupting
the data.
It exists when it is possible to make changes in the file
structure without affecting the application program’s ability to access.
Data Inconsistency
Data inconsistency exists when different and conflicting
versions of the same data appear in different places. For, example, suppose you
change an agent’s phone number or city in the AGENT file. If you forget to make
corresponding changes in the CUSTOMER file, the files contain different data
for the same agent. Reports will yields inconsistent results depending on which
version of the data is used.
Data Anomalies
The data dictionary defines anomaly as “an abnormally”.
Ideally, a field value change should be made in only a single place. Data
redundancy, however, fosters an abnormal condition by forcing field value
changes in many different locations. Look at the CUSTOMER file inIf agent Virat decides to get married and move, the agent name, city is likely
to change. Instead of making just a single name and/or city change in a single
file (AGENT), you must also make change each time that agent’s name, city occur
in the CUSTOMER file. You could be faced with the prospect of making hundreds
of corrections, one for each of the customers served by that agent! The same
problem occurs when an agent decides to quit. Each customer served by that
agent must be assigned a new agent. Any changes in any field value must be
correctly made in many places to maintain data integrity. A data anomaly
develops when all of the required changes in the redundant data are not made
successfully.·
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