What is Data Inconsistency in DBMS?

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.

What is Data Inconsistency?

Data inconsistency is the scenario in DBMS where there are more than 2 tables within a database that work with the same data but receive it from different inputs. In simpler words, Data Inconsistency is the concept where there are conflicts or different copies of the same data in the database. This issue occurs when data stored in different locations within the database do not match or are not synchronized. The possibilities through which this occurs are software bugs, human errors, hardware failures, and many more situations.

Let’s understand the concept of Data Inconsistency through an example:

Example of Data Inconsistency:

Consider a situation where an organization maintains multiple databases for different departments. The Financial Table stores the employee’s salary data, while Human Resources Table consists of employee records and salaries.

Now, let’s assume that there is a system that is used for synchronizing or sending data from both tables into a Target Database. Due to a technical issue, the synchronization process fails to detect the data inconsistency, which results in the conflict records as shown in the above diagram in Target Database.

We can easily notice that John’s salary is repeated twice in Target Database with different values. This data inconsistency arose due to the synchronization process did not reconcile the conflicting salary values for John in the Financial and Human Resource tables.

Problems Caused Due to Data Inconsistency

Data Inconsistency can lead to various problems that are as follows:

1. Data Integration problems: Data Inconsistences compromises the integrity aspect of the data stored in the database, due to this it becomes difficult to rely or trust on the information.
2. Increased Complexity: If the size of the database is huge then resolving the data inconsistencies needs to compromise additional time and effort. Also, additional resources are required to solve the inconsistencies. This adds complexity to database maintenance and administrative tasks.
3. Data Duplication: Inconsistencies lead to the problem of duplicate data entries, which not only waste storage memory but also increments the probability of future inconsistencies of records or data.
4. Incorrect Reporting: Inconsistent data can generate inaccurate results and reports. In the analytical process, a flawed- decision can be taken due to unreliable information passed as the input to the decision-making process.

Disadvantages of Inconsistent Data

Below are the disadvantages of Inconsistent Data in DBMS:

1. Decrement in Productivity: Working with Inconsistent Data needs manual intervention and troubleshooting processes, which leads to a decrement in productivity and direct effects on operational costs.
2. Impaired Decision-Making: Inconsistent Data undermines the ability to generate informed decisions based on reliable information, which potentially weakens the business outcomes or insights.
3. Reduced Data Quality: Several decision-making processes rely on the factor of Data Quality, Incosistent data compromises the quality of the database and makes it less accurate and less reliable.
4. Customer Dissatisfaction: Customer Satisfaction is the overall aim of each organization and company, Inconsiteny in data can directly affect and impact customer experience, like incorrect billing, shipping issues, etc problems resulting in customer dissatisfaction.

FAQs: 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.