Validation checks are a type of data quality control that helps to ensure the integrity of data for a system interface. Validation checks verify that the data entered or transferred between systems is correct, consistent, and conforms to predefined rules or standards. Validation checks can prevent or detect errors, anomalies, or inconsistencies in the data that may affect the system’s functionality, performance, or security.
Option C is correct because validation checks are a common and effective method of ensuring data integrity for a system interface. Validation checks can be performed at various stages of the data lifecycle, such as input, processing, output, or storage. Validation checks can also be applied to different types of data, such as data types, codes, ranges, formats, consistency, and uniqueness.
Option A is incorrect because system interface testing is a type of software testing that verifies the interaction between two separate systems or components of a system. System interface testing does not directly ensure the integrity of data for a system interface, but rather the functionality and reliability of the interface itself. System interface testing may use validation checks as part of its test cases, but it is not the same as validation checks.
Option B is incorrect because user acceptance testing (UAT) is a type of software testing that evaluates whether the system meets the user’s expectations and requirements. UAT does not directly ensure the integrity of data for a system interface, but rather the usability and acceptability of the system from the user’s perspective. UAT may use validation checks as part of its test scenarios, but it is not the same as validation checks.
Option D is incorrect because audit logs are records of events and activities that occur within a system or network. Audit logs do not directly ensure the integrity of data for a system interface, but rather provide evidence and accountability for the system’s operations and security. Audit logs may use validation checks as part of their analysis or reporting, but they are not the same as validation checks.
[References:, CISA Online Review Course1, Module 5: Protection of Information Assets, Lesson 4: Data Quality Management, slide 5-6., CISA Review Manual (Digital Version)2, Chapter 5: Protection of Information Assets, Section 5.3: Data Quality Management, p. 281-282., CISA Review Manual (Print Version), Chapter 5: Protection of Information Assets, Section 5.3: Data Quality Management, p. 281-282., CISA Questions, Answers & Explanations Database3, Question ID: QAE_CISA_722., Data Validation - Overview, Types, Practical Examples4, Data Validity: The Best Practice for Your Business5, Validation - Data validation6, What is Data Validation? Types, Techniques, Tools7, , , , , , ]