Redundancy means duplicacy of data or repetitive data. In distributed database case the data is stored in different systems . So the answers is yes there can be redundancy of records / data.In distributed database , data is stored in different systems. Since the data is distributed there is redundancy of records.
its called data redundancy.
Database is collection of some inter related records . And yes, data redundancy be completely eliminated when database approach is used.
A database is a collection of interrelated data and the advantages of a database are ensured efficiency, standardized data, maintainable data, integrated data, reduced redundancy of data.
Storing the information several time leads to waste of storage space is called data redundacy. Data redundancy is a term used about databases and means simply that some data fields appear more than once in the database. Data redundancy is wasteful and inefficient for several reasons and database designers attempt to eliminate it as far as possible by using a technique called data normalization. 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.
In database there are number of issues to be handled ,like redundant data, inconsistent data, unorganized data etc. Redundancy of data is the repetitive data that is taking the storage unnecessarily . So the redundant data must be removed or at least reduced.
Normalization is the process of organizing data in a database to reduce redundancy and dependency. The objective of normalization is to minimize data redundancy, ensure data integrity, and improve database efficiency by structuring data in a logical and organized manner.
In database we store data however the can be redundant. Redundancy means repetitive data that is taking extra storage space . So to reduce or prevent the storage space we should eliminate redundancy or just reduce it.
data redundancy
DBMS stands for database management system. DBMS reduce data redundancy as it checks if the data is duplicate and if duplicate then store it as a single record.
This statement is incorrect. Data redundancy refers to storing the same piece of data in multiple places, leading to inefficiency and inconsistency. A group of related fields is known as a database or a record in a database.
When there are several instances of the same data, it is referred to as "data redundancy." This occurs when identical pieces of information are stored in multiple places, which can lead to inefficiencies and inconsistencies in data management. Redundancy can be intentional for backup purposes or unintentional due to poor database design. Reducing data redundancy is often a goal in database normalization.