Explanation:

Since a customer can be both a loan applicant and a high net worth customer, the best approach is to:

- Ingest the data into two separate Data Lake Objects (DLOs)—one for loan applicants and one for high net worth customers.
- Map each DLO to the Individual and Contact Point Email Data Model Objects (DMOs) to ensure proper identity resolution and avoid duplicate records.
This method ensures:

- Accurate identity resolution by linking records correctly.
- Better segmentation and activation for different customer categories.
- Avoiding unnecessary duplication while maintaining distinct data sources.


❌ Why the other options are incorrect:

A. Use a data transform to consolidate the data into one DLO and then map it to the individual and Contact Point Email DMOs.
❌ This would mix source contexts before identity resolution, reducing traceability and flexibility. It's not best practice.
C. Ingest the data into two DLOs and then map to two custom DMOs.
❌ Using custom DMOs is unnecessary here. Standard DMOs (Individual, Contact Point Email) are designed for this use case.
D. Ingest the data into one DLO and then map to one custom DMO.
❌ Again, this loses source context and bypasses the benefits of using standard identity resolution.