ISACA Certified Information Systems Auditor (CISA) ExamDomain 4: Information Systems Operations and Business ResilienceMedium
An IS auditor is evaluating an organization's data management practices, specifically focusing on data quality. The auditor notes that data entry operators frequently input incomplete or inconsistent customer information, such as missing addresses or inconsistent naming conventions. There are no automated validation checks or mandatory fields at the point of entry. Which of the following is the MOST significant long-term consequence of this practice?
- AHigher training costs for data entry personnel.
- BDifficulty in generating accurate management reports and business intelligence.
- CReduced system processing speed due to data anomalies.
- DIncreased storage requirements for redundant data.
Show answer & explanationAnswer & explanation
Correct answer: B. Difficulty in generating accurate management reports and business intelligence.
Incomplete and inconsistent data directly compromises data quality. Over time, this 'dirty data' makes it extremely difficult, if not impossible, to generate reliable and accurate reports, perform meaningful data analysis, or derive sound business intelligence, leading to poor decision-making.
Why the other options are wrong
- A. Training can help, but the lack of automated controls is the root cause, and the consequence is data quality, not just training costs.
- C. Data anomalies primarily impact logical processing and analysis, not necessarily raw system speed unless the anomalies are extreme.
- D. While possible, the primary impact of inconsistent data isn't storage, but its usability.
Data Quality Controls
Mechanisms and processes implemented to ensure the accuracy, completeness, consistency, validity, and timeliness of data throughout its lifecycle.
- Includes validation rules, mandatory fields, and data cleansing.
- Essential for reliable reporting and decision-making.
- Reduces errors and improves data integrity.
Memory trick: Garbage in, garbage out: bad data makes bad decisions.