adsense analytic

Friday, April 6, 2012

Data Redundancy, Inconsistency . . . .

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.·      

No comments:

Post a Comment