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yes. data redundancy is where there is duplication of data in a database. when this happens, anyone who has to make updates to a table in a database (that is, make changes to the database) will have to change that particular data that has been duplicated so many times in so many places. this creates a problem and it is not always going to be possible for a person to change everything correctly. this therefore leads to inconsistencies in the database. hope this helps.
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What is the difference between data redundancy and data inconsistency?
Redundancy is data that is not needed or no longer needed. Inconsistency is where you have different data for what should be the same thing, as a result of one piece of data having a few copies and not all of them being updated. So if someone's address is on a system several times, and then their address changes, but it is only updated in some of those places, then the person will have both their old and new address on the system. The data is not consistent then. To avoid this data should be only stored once and everyone that needs it looks at the one set, rather than each having their own copy.
What is difference between the data validation and data redundancy?
one is a validation the other is redundancy clue is in the name
When data change in multiple list and all list are not updated then it called?
Data inconsistency
What are the disadvantages of data redundancy?
with data redundancy there willbe more wastage of memory space as same type of data willbe saved many times when to want to see the data all duplicate results will come
What does Data Redundancy mean in database design?
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.
What is data redundancy and problems associated with it?
Duplication of data is data redundancy. It leads to the problems like wastage of space and data inconsistency.
The problem of inconsistency in data is a direct result of?
The problem of inconsistency in data can arise from various factors such as errors in data entry, lack of standardized data formatting, and incomplete data updates. Inconsistent data can lead to inaccurate analysis and decision-making, affecting the overall reliability of data-driven processes.
What are a couple of problems whit a traditional file environment?
Data redundancy Lack of data redundancy Data inconsistency Data security
What is data inconsistency?
Data inconsistency exists when different and conflicting versions of the same data appear in different places. Data inconsistency creates unreliable information, because it will be difficult to determine which version of the information is correct. (It's difficult to make correct - and timely - decisions if those decisions are based on conflicting information.) Data inconsistency is likely to occur when there is data redundancy. Data redundancy occurs when the data file/database file contains redundant - unnecessarily duplicated - data. That's why one major goal of good database design is to eliminate data redundancy.
What is redundancy and inconsistency in data base management system?
Redundancy in a database occurs when the same piece of data is unnecessarily stored in multiple places, leading to inefficiency and potential data inconsistencies. Inconsistency arises when different copies of the same data do not match due to errors or failure to update all instances simultaneously, impacting data integrity and reliability. Database management systems aim to reduce redundancy and ensure consistency through normalization and transaction processing techniques.
What is data redundancy?
Data redundancy refers to the unnecessary duplication of data in a database or system. It can cause inefficiencies, make updates more difficult, and increase storage requirements. Data redundancy can be minimized through normalization techniques in database design.
What is Drawbacks of using file system to store data?
* Data redundancy and inconsistency. * Data isolation * Problem in atomicity of data * Difficulty to access data. * Security Problems
When the same data are stored in many places?
Data redundancy
Advantage of an Oracle Database system?
Advantages provided by a database system are : a) Redundancy of data is reduced. b) Secured data. c) Controlled data inconsistency. d) Integrated data. e) Standardized data
What are the disadvantages of traditional file management?
Data Redundancy and Inconsistency: Data redundancy: The presence of duplicate data in multiple data files so that the same data are stored in more than one place or location. Data inconsistency: The same attribute may have different values. Program-Data dependency The coupling of data stored in files and the specific programs required to update and maintain those files such that changes in programs require changes to the data. Lack of flexibility A traditional file system can deliver routine scheduled reports after extensive programming efforts, but it cannot deliver ad-hoc reports or respond to unanticipated information requirements in a timely fashion.
What is the difference between data redundancy and data inconsistency?
Redundancy is data that is not needed or no longer needed. Inconsistency is where you have different data for what should be the same thing, as a result of one piece of data having a few copies and not all of them being updated. So if someone's address is on a system several times, and then their address changes, but it is only updated in some of those places, then the person will have both their old and new address on the system. The data is not consistent then. To avoid this data should be only stored once and everyone that needs it looks at the one set, rather than each having their own copy.
Advantages and disadvantages of External database?
Dis Advantages: Security may be compromised without good controls, Extra hardware may be required, System is likely to be complex Advantages: Reduced data redundancy, Secured data, Integrated data, Controlled data inconsistency
