Data integrity can be compromised through which of the following?
Question 84 options:
a) Cleaning dirty data
b) Human error or hackers
c) Transmission errors
d) Human error or hackers and transmission errors
The correct answer and explanation is :
The correct answer is d) Human error or hackers and transmission errors.
Explanation:
Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle. It ensures that the data is correct, consistent, and available for processing or analysis. Several factors can compromise data integrity, including:
- Human Error or Hackers:
- Human Error: Mistakes made by individuals can compromise data integrity. This could include typing errors, incorrect data entry, or misunderstanding instructions for data handling. For example, an employee may accidentally delete important records or input incorrect data into a database. Additionally, human mistakes can occur during manual data transfers or conversions.
- Hackers: Malicious actors, such as hackers, can also jeopardize data integrity. Hackers may manipulate, alter, or delete data intentionally to damage a system, steal sensitive information, or disrupt services. They can exploit vulnerabilities in data storage systems or transmission protocols to gain unauthorized access to the data. Data breaches, where hackers alter or steal data, are common examples of threats to data integrity.
- Transmission Errors:
- Transmission Errors: Data transmission involves sending data from one system to another over networks, such as the internet or internal networks. During this transfer, the data may become corrupted or altered due to various factors like signal interference, network congestion, or hardware malfunctions. For instance, a file might get corrupted if there’s an interruption in the transmission process, leading to loss or alteration of its contents, thereby compromising its integrity.
When data is transmitted, stored, or processed, it is susceptible to errors or attacks from multiple sources. While cleaning dirty data (option a) is crucial for improving data quality, it does not directly compromise data integrity—rather, it helps ensure data quality is maintained.
In conclusion, the correct answer is option d, as both human errors, malicious hacking activities, and transmission issues can all significantly affect data integrity.