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What is data redundancy and data integrity?
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. In the below link you can find more details. http://opencourseware.kfupm.edu.sa/colleges/cim/acctmis/mis311/files%5CChapter1-Database_Systems_Topic_2_Introducing_Databases.pdf
Which characteristics you will consider while selecting a data structure?
# Do you need random access to the data? # Does the data need to be ordered? # Can there be duplicate entries? # Are you more interested in reading from or writing to the data structure? # Are you more interested in data access speed or data storage size?
What is an example of fail safe principle of redundancy?
There is a school of thought residing with how much redundancy should be built in. obviously more redundancy should make it more reliable however those same additional parts could make the system fail as a consequence of additional redundancy.
Is the cyclic redundancy check better than hamming code?
It depends on what you are doing. The cyclic redundancy check will only detect an error, while the hamming code can also correct many types of errors. However to perform this correction the extra error detection parity bits required in hamming code are many more than the bits needed for cyclic redundancy check, per data byte being checked. Normally cyclic redundancy check is done on large block of data that can be resent or retried to get the correct block of data (e.g. telecommunication channels, disk sectors). Normally hamming code is done on individual bytes or words of computer memory.
What does data type mean in I.C.T.?
Data is stored in databases. To make the database more efficient, different types of data are usually classified as a certain 'data type'.
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.
How is data redundancy reduced?
Data redundancy can be reduced by normalizing the database to eliminate duplicate data, creating relationships between tables, and using foreign keys to link related information. Using data validation rules and constraints can also help prevent redundant data from being entered into the database. Implementing a master data management strategy can centralize and standardize data, reducing redundancy across different systems.
What is Data redundancy in DBMS?
Data redundancy in DBMS refers to the duplication of data within a database system. This can result in inconsistencies and inefficiencies, as well as consuming more storage space. It is important to minimize data redundancy in order to maintain data integrity and improve performance.
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
When you store the same data in more than one place?
Storing the same data in more than one place is known as data replication. This practice is often employed to improve data availability, reliability, and performance in distributed systems by ensuring redundancy and minimizing the risk of data loss in case of failures. However, it can also introduce complexity in data synchronization and consistency.
Storing the same data in more than one place is called?
Redundancy.
What does data redundancy mean?
Data redundancy: Sometime Data redundancy refers to in computer data storage, is a property of some disk arrays which provides fault tolerance, so that all or part of the data stored in the array can be recovered in the case of disk failure. The cost typically associated with providing this feature is a reduction of disk capacity available to the user, since the implementations require either a duplication of the entire data set, or an error-correcting code to be stored on the array.Redundancy is attained when the same data values are stored more than once in a table, or when the same values are stored in more than one table.One of the biggest disadvantages of data redundancy is that it increases the size of the database unnecessarily.
What is the difference between file base system and data base system?
DBS has more security and data integrity.It reduce data redundancy and updating errors which can occur in FBS.Contains of concurrent data access.But also it's expensive to use and they are also complex.Damage to DB affects virtually all application programs.
What is redundancy and is it good or bad ina database?
Redundancy is when you have the same data in multiple locations. Some redundancy is good, while too much is bad. If two departments are using the exact same data, then this redundancy is bad. It is utilizing excess resources. Redundancy, can be used as a failsafe. Having a backup helps incase of data corruption. The key is too find the right balance of redundancy within a database.
What is data redundancy and data integrity?
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. In the below link you can find more details. http://opencourseware.kfupm.edu.sa/colleges/cim/acctmis/mis311/files%5CChapter1-Database_Systems_Topic_2_Introducing_Databases.pdf
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.
Which characteristics you will consider while selecting a data structure?
# Do you need random access to the data? # Does the data need to be ordered? # Can there be duplicate entries? # Are you more interested in reading from or writing to the data structure? # Are you more interested in data access speed or data storage size?
