What capability does the computeRelative transformation provide?

The computeRelative transformation is designed to add fields that reflect the differences or ratios between the current record and specified preceding or succeeding records within a dataset. This capability is particularly useful for various types of analysis, such as calculating changes over time or comparing values in a sequential manner, which aids in understanding trends or performance metrics.

When using computeRelative, analysts can derive insights based on previous and next records, enabling them to identify patterns, anomalies, or shifts in data that might be relevant for decision-making. This is especially important in time series analysis or when comparing items in a sequence where the relationship between adjacent records holds significance.

The other options focus on capabilities that are not directly related to what computeRelative does. For instance, the ability to analyze across different datasets or combine multiple datasets involves different transformations or join operations in analytics. Similarly, calculating averages typically falls under aggregation functions rather than the relative computations that computeRelative performs. Therefore, the unique function of computeRelative in adding fields based on previous and next records is what sets it apart.