Data Consistency and Inconsistency - What is Difference
Data Consistency:
Definition 1:
Data consistency means that the
changes made to the different occurrences of data should be controlled
and managed in such a way that all the occurrences have the same value
for any specific data item. Data inconsistency leads to a number of
problems, including loss of information and incorrect results. In the
database approach, it is controlled because data is shared and
consistency is controlled and maintained.
Data Consistency Definition 2:
Data consistency
meaning is the validity, accuracy and usability of related data. It
ensures that each user observes a consistent(Same) view of the data,
including changes made by the user’s own transactions and transactions
of other users.
Types of Data Consistency:
- Point in time consistency
- Transaction consistency
- Application consistency
Data Inconsistncy:
Data Inconsistency Definition: Data inconsistency meaning is that different versions of the same data appear in different places. (like you store name of user in every table instead of their ID).
For example, the ZIP code is saved in one table as 0000-000 numeric data format; while in another table it may be represented in 0000000.
What is Inconsistent Problem:
Inconsistent problems occurred when there is data redundancy and data redundancy occurs when the data file/database file contains redundant – unnecessarily duplicated data.
Redundant Data or Redundancy in DBMS:
Definition 1:
Redundancy means “Duplicate data is
available in different tables. e.g. a company is neglecting
normalization and save names instead of ID in tables. This cause the
problem of wastage of storage and redundancy which is the cause of
inconsistency.
Definition 2: red question answers area.
Redundancy Data Example:
Consider the example of table Organizer where names are stored multiple times (we can use normalization and store the organizer ID instead of name). Just like that store meeting slots and test location and meeting with as ID to save redundancy.
| Redundant/Inconsistent Data Example | |||||
| ID | Organizer | Date | Test Location | Meeting | Meeting With |
|---|---|---|---|---|---|
| 1 | John Smith | 20-01-2021 | Bermingham | Evening | Rosina |
| 2 | John Doe | 20-01-2021 | Mexico | Evening | Rosina |
| 3 | John Doe | 20-01-2021 | Mexico | Evening | Rosina |
| 4 | John Doe | 20-01-2021 | Mexico | Evening | Rosina |
| 5 | John Doe | 20-01-2021 | Mexico | Evening | Rosina |
| 6 | John Smith | 20-02-2021 | Bermingham | Evening | Rosina |
FAQ – Data Consistency and Data Inconsistency
Data that is either stored in several tables at the same time or occurs more than once within a table. They increase the amount of data considerably because the same data has to be saved multiple times, which is superfluous.
Normalization is a technique to save ourselves from redundancy.
e.g. if we have a table where we fill “posted by” column and save the name of user instead of his “ID“. The maintenance is lengthy process and we have inconsistent data.
If we didn’t use normalization technique our storage will be waste. So in order to safe ourselves from inconsistency avoid redundant data.
Yes, by normalization our database tables you can get consistent data.
The update command in Database will get longer time and may be you can crash your database by updating long tables.
Yes, a database must have consistent data to avoid the problems of redundancy and inconsistency. That is why we called consistency and inconsistency are interrelated.
Difference Between Data redundancy and Data inconsistency?
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