Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud. Based on this, a calculated…

The correct operational sequence in Data Cloud ensures data flows logically from ingestion to enrichment and activation. First, the Refresh Data Stream process must run to ingest the new daily data from the Amazon S3 bucket into Data Lake Objects (DLOs). Second, Identity Resolution must run to process this new data, matching and reconciling it to create or update unified customer profiles. Finally, the Calculated Insight is run on these updated unified profiles to compute the "total spend per customer," making the fresh metric available for use in segmentation.

1. Salesforce Help

"Orchestrate and Automate Data Cloud Processes": This document outlines the typical sequence for automating Data Cloud jobs. It provides an example: "...create a flow that refreshes a data stream

runs identity resolution

and then runs a calculated insight." This directly supports the sequence in option A.

2. Salesforce Help

"Calculated Insights": This documentation specifies the objects on which Calculated Insights can be built: "You can build calculated insights on data lake objects (DLOs)

data model objects (DMOs)

and unified objects." To calculate a metric "per customer

" the unified object

which is the output of Identity Resolution

is required. This confirms Identity Resolution must precede the Calculated Insight.

3. Salesforce Help

"Identity Resolution": This documentation explains that Identity Resolution processes data from Data Model Objects (DMOs)

which are populated by data streams. It states

"Identity resolution uses matching and reconciliation rules to link disparate data sources into a single unified profile..." This confirms that data ingestion via a data stream refresh must occur before Identity Resolution can run on new data.