A rideshare company wants to send an email to customers that provides a year-in-review with five "fun" trip statistics, such as destination, distance…

A data transform is the most appropriate solution for this use case. It allows for the aggregation of raw, row-based data (individual trips) into summary statistics using a single SQL query. This is ideal for a point-in-time, campaign-specific requirement like a "year-in-review." The output of the transform is a new Data Lake Object (DLO) where each row represents a customer and the columns contain their five personalized statistics. This DLO is then mapped to the Individual Data Model Object, making the aggregated statistics available as direct attributes for easy personalization within the activation target (e.g., Marketing Cloud Engagement). This approach correctly centralizes the data processing within Data Cloud, which is a fundamental best practice.

1. Salesforce Help

"Data Transforms in Data Cloud": This document outlines the purpose of data transforms: "A data transform lets you transform your data to a desired structure. Write a data transform using SQL to... combine and transform data from one or more data lake objects." This directly supports using a transform to aggregate the raw ride data into the required summary statistics.

2. Salesforce Help

"Data Mapping": This resource explains the process of mapping fields from a source object (like the DLO created by the data transform) to a target Data Model Object (DMO)

such as the Individual DMO. This is the necessary step to make the aggregated statistics available on the customer profile for activation. (See section: "Map Your Data").

3. Salesforce Help

"Calculated Insights": This documentation describes Calculated Insights as a feature to "define and calculate multidimensional metrics." The examples provided

such as RFM scores

emphasize their use for ongoing

reusable profile enrichment rather than ad-hoc

campaign-specific data preparation

making the Data Transform a more direct tool for the scenario. (See section: "Calculated Insights Use Cases").