Which of the following is NOT a cause of data quality issues from data processing?

Which of the following is NOT a cause of data quality issues from data processing?

• A. Incorrect assumptions about data sources
• B. Changes to data structures
• C. Inconsistent data entry interfaces
• D. Stale business rules

Answer: (C)

In the context of data processing, the focus is often on how various practices and systems influence the quality of data. While inconsistent data entry interfaces can create challenges, they do not inherently lead to data quality issues during the processing of data. Instead, they may result in operational inefficiencies or frustration among users but may not directly compromise the integrity or accuracy of the data being processed. On the other hand, incorrect assumptions about data sources can lead to misinterpretations and misuse of data, resulting in quality issues. Changes to data structures can disrupt the relationships and schemas expected for data processing, leading to errors and inconsistencies. Stale business rules can cause data to be processed in ways that no longer reflect current requirements or realities, resulting in poor data quality. Therefore, it is primarily the inconsistent interfaces that influence user experience, rather than creating fundamental issues in the quality of the data produced during processing.

In the context of data processing, the focus is often on how various practices and systems influence the quality of data. While inconsistent data entry interfaces can create challenges, they do not inherently lead to data quality issues during the processing of data. Instead, they may result in operational inefficiencies or frustration among users but may not directly compromise the integrity or accuracy of the data being processed.

On the other hand, incorrect assumptions about data sources can lead to misinterpretations and misuse of data, resulting in quality issues. Changes to data structures can disrupt the relationships and schemas expected for data processing, leading to errors and inconsistencies. Stale business rules can cause data to be processed in ways that no longer reflect current requirements or realities, resulting in poor data quality. Therefore, it is primarily the inconsistent interfaces that influence user experience, rather than creating fundamental issues in the quality of the data produced during processing.