What is the primary purpose of calculated fields in Splunk?

The primary purpose of calculated fields in Splunk is to facilitate data calculation and transformation. Calculated fields allow users to derive new fields from existing data based on expressions or functions defined in the Splunk interface. This helps in enhancing and manipulating the data set according to specific analytical needs.

For instance, if you have a numeric field representing sales and you want to calculate tax or total revenue, you can create a calculated field to automatically perform these calculations without altering the raw data. This dynamic aspect of calculated fields is essential for users who need customizable data views for reporting and analysis.

The other choices relate to important aspects of data handling but do not capture the main functionality of calculated fields as effectively. Data cleansing focuses on removing inaccuracies from data sets, event categorization deals with organizing data into meaningful categories, and data normalization pertains to standardizing data formats. While these processes are valuable within a data pipeline, they are not the primary role of calculated fields, which specifically support the calculation and transformation processes.