Data Inconsistency

1. What are the common causes of Data Inconsistency?

Some of the common causes of Data Inconsistency are Hardware Failures, Network Issues, Improper Data Synchronization, and Human Errors. Along with this, Concurrent Transactions into a database can also lead to Data Inconsistency.

2. How can Data Inconsistency prevent?

Data inconsistency can be prevented by applying data validation rules, performing regular data audit processes, using transactions and locking mechanisms for maintaining data integrity and enforcing referential integrity.

3. What is the difference between Data Inconsistency and Data Redundancy?

Data inconsistency is the term that refers to mismatched data values in DBMS, whereas data redundancy refers to the unwanted repetition of data in different locations.

4. Can Data Inconsistency be fixed once it occurs?

Yes, Data Inconsistency can be fixed and resolved by detecting inconsistencies, updating or deleting redundant entries, and ensuring data synchronization across all database records.

The database is the collection of structured records that are used in various scenarios to gain useful insights, perform CRUD operations, and many other things. The data stored in the Database is in the form of rows and columns, we mostly call them as records. There are various tables that store and represent the data/records to the user. In these tables, there may be a situation where the data stored as records may be inconsistent. This leads to Data Inconsistency in the database. In this article, we will explore the concept of Data Inconsistency, will understand the concept through a simple example, explore the problems caused due to Data inconsistency, and lastly will see the disadvantages of Inconsistent Data.