What transformation can be applied to obtain the hour from a timestamp for analysis?

To extract the hour from a timestamp for analysis, applying a field transformation is the correct approach. Field transformation involves modifying the structure or format of individual data fields in a dataset. In this context, you would be transforming a timestamp field to isolate the hour component, which is crucial for time-based analyses, such as trends by hour or peak usage times.

This transformation can typically be done through various functions in data analysis tools or programming languages, which can take the full timestamp and return just the hour part. This is fundamentally a change in how the data is represented without altering the underlying data type.

The other options present different concepts not relevant to simply extracting the hour from a timestamp. Data normalization refers to adjusting values in a dataset to a common scale, outlier detection focuses on identifying anomalies in data, and date standardization deals with making date formats uniform across a dataset. None of these processes directly apply to extracting the hour from a timestamp.