Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
ISACA Certified in Risk and Information Systems Control · Isaca
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
The answer is: D. Periodically reviewing big data strategies In an organization where data analytics plays a crucial role in decision-making, it's important to ensure that the data is accurate and reliable. Periodically reviewing big data strategies can help identify any issues with data quality, sourcing, and processing, thus helping to minimize the risk associated with inaccurate data. Evaluating data sources for vulnerabilities (Option A) is important but focuses more on security rather than accuracy. Establishing an intellectual property agreement (Option B) would likely not address the issue of data accuracy. Benchmarking to industry best practice (Option C) could help improve processes but may not directly address the specific risk of inaccurate data. Therefore, the periodic review of big data strategies is the best choice for ensuring data accuracy and minimizing associated risks.
Vulnerabilities don’t just refer to security; they also include integrity issues, inconsistencies, and source credibility all of which impact data accuracy
A. Evaluating each of the data sources for vulnerabilities By thoroughly evaluating each data source for vulnerabilities, you can identify potential weaknesses and data quality issues early in the data collection and integration process. This allows you to implement appropriate data cleansing, validation, and quality assurance measures. Ensuring the accuracy and reliability of your data sources is a fundamental step in minimizing the risk of inaccurate data negatively impacting decision-making. While establishing intellectual property agreements (B), benchmarking to industry best practices (C), and periodically reviewing big data strategies (D) are important aspects of managing data-related risks, they do not directly address the issue of inaccurate data at the source, which is crucial for data-driven decision-making.