What action can you take if Fortianalyzer includes an existing data set that is similar to your needs?

When faced with the need to create a data set in Fortianalyzer, choosing to clone or modify an existing one is a practical and efficient approach. This option allows you to leverage the foundation of the existing data set that closely matches your requirements, reducing the time and effort needed to build a new set from the ground up.

Cloning or modifying an existing data set enables adjustments such as updating parameters, filtering data, or adding new variables that align with your specific objectives. The process is often less resource-intensive because it uses the structure, format, and underlying data already established. This not only speeds up the data set creation process but also helps ensure consistency and accuracy, as you are building upon a proven framework.

Creating a new data set from scratch would be far more time-consuming and might lead to inconsistencies if the changes made are not based on a reliable reference. Ignoring the existing set misses out on valuable insights and potentially useful data that could simplify your efforts. Requesting additional help may be unnecessary in this context, especially when you have the option to modify an existing asset that meets your needs closely.