Field aliases are primarily used to achieve which of the following?

Field aliases are primarily used to normalize data within Splunk. Normalization refers to the process of making data consistent and uniform across different sources. By using field aliases, users can assign a common name to different fields that represent the same type of data but may have different names across various datasets. For instance, if one dataset has a field named "src_ip" and another has "source_ip," creating a field alias allows you to refer to both fields with a single common name, thereby streamlining searches and reports.

While other options like "clean data," "transform data," and "calculate data" represent important aspects of data management, they do not accurately capture the primary function of field aliases. Cleaning data typically involves removing inaccuracies or duplicates, transforming data may refer to changing the format or structure, and calculating data involves performing mathematical operations. None of these tasks are the primary goal of field aliases, which focus specifically on achieving normalization for consistent usage in searches and analyses.