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Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users. What should the consultant do to accomplish this?
A. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.
B. Use formula fields based on the Account Country field to filter incoming records.
C. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
D. Use the data spaces feature and apply filtering on the Account data lake object based on Country.
A customer has a calculated insight about lifetime value. What does the consultant need to be aware of if the calculated insight needs to be modified?
A. New dimensions can be added.
B. Existing dimensions can be removed.
C. Existing measures can be removed.
D. New measures can be added.
Which three actions can be applied to a previously created segment?
A. Reactivate
B. Export
C. Delete
D. Copy
E. Inactivate
Explanation:
These three actions can be applied to a previously created segment. You can export a segment to a CSV file, delete a segment from Data Cloud, or copy a segment to create a duplicate segment with the same criteria.
During discovery, which feature should a consultant highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile?
A. Data Cleansing
B. Harmonization
C. Data Consolidation
D. Identity Resolution
A client wants to bring in loyalty data from a custom object in Salesforce CRM that contains a point balance for accrued hotel points and airline points within the same record. The client wants to split these point systems into two separate records for better tracking and processing. What should a consultant recommend in this scenario?
A. Clone the data source object.
B. Use batch transforms to create a second data lake object.
C. Create a junction object in Salesforce CRM and modify the ingestion strategy.
D. Create a data kit from the data lake object and deploy it to the same Data Cloud org.
Explanation:
Batch transforms are a feature that allows creating new data lake objects based on existing data lake objects and applying transformations on them. This can be useful for splitting, merging, or reshaping data to fit the data model or business requirements. In this case, the consultant can use batch transforms to create a second data lake object that contains only the airline points from the original loyalty data object. The original object can be modified to contain only the hotel points. This way, the client can have two separate records for each point system and track and process them accordingly.
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