Periodically reviewing big data strategies is the best option to minimize the risk of inaccurate data, because it allows the organization to assess the quality, validity, and reliability of the data sources and the analytics methods. It also enables the organization to identify and address any gaps, errors, or inconsistencies in the data and the results. By reviewing the big data strategies, the organization can ensure that the data analytics are aligned with the business objectives and the risk appetite.

Establishing an intellectual property agreement is not relevant to the risk of inaccurate data, as it is a legal measure to protect the ownership and use of the data, not its quality or accuracy.

Evaluating each of the data sources for vulnerabilities is a good practice, but it is not sufficient to minimize the risk of inaccurate data, as it only focuses on the security aspect of the data, not the validity or reliability of the data itself.

Benchmarking to industry best practice is a useful way to compare the performance and results of the data analytics, but it does not directly address the risk of inaccurate data, as it assumes that the data and the methods are already valid and reliable. References = Risk IT Framework, 2nd Edition, ISACA, 2019, page 62-63.