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SAP Certified Associate - Implementation Consultant - SAP Customer Data Platform Sample Questions (Q30-Q35):

NEW QUESTION # 30
On which level of a B2B data model should a role (for example, Sales Manager or CEO) of a B2B customer be stored?

A. Customer Profile
B. Relationship
C. Segment
D. Group

Answer: B

NEW QUESTION # 31
Which of the following can be used as audience conditions?
Note: There are 3 correct answers to this question.

A. Event
B. Indicator
C. Segment
D. Profile attribute
E. Action

Answer: B,C,D

NEW QUESTION # 32
Which of these activation methods can be used with actions?
Note: There are 2 correct answers to this question.

A. Audiences
B. CX milestones
C. CX journeys
D. CX flows

Answer: C,D

Explanation:
The SAP Customer Data Platform is designed to manage customer data across different levels of organization. A tenant represents an instance of the platform provisioned for an organization, and within this tenant, multiple workspaces can be created. These workspaces serve as separate environments for development and production purposes. Additionally, a business unit, which is a logical partition within a workspace, can also contain multiple workspaces, allowing for further segmentation and management of customer data within the same organizational unit.
Reference = This relationship is outlined in the SAP Customer Data Platform documentation available on the SAP Help Portal, which provides comprehensive information on the configuration and management of tenants, workspaces, and business units12.

NEW QUESTION # 33
A known customer buys a TV that is delivered late. SAP Customer Data Platform is configured to ingest the customer data for late deliveries so that the business can react and keep good customer satisfaction metrics.
Which type of customer profile is best to use in this scenario?

A. Contextual Customer Profile
B. Unified Customer Profile
C. Customer Context Profile
D. Customer Activity Profile

Answer: B

NEW QUESTION # 34
Which of the following merge rules must be defined at attribute level? Note: There are 2 correct answers to this question.

A. Decide whether to concatenate the incoming value with the existing value of the same attribute
B. Decide whether to override existing data, based on the quality of the incoming and existing data
C. Decide whether more than one value can be saved for an attribute
D. Decide what to do if a data conflict occurs for an identifier attribute

Answer: A,B

Explanation:
In the SAP Customer Data Platform, merge rules at the attribute level are essential for managing how incoming data is integrated with existing data. For an attribute, you can define whether to concatenate the incoming value with the existing value, which is crucial when you want to preserve all historical data points for a particular attribute. Additionally, you can set rules to decide whether to override existing data with incoming data based on their respective data quality. This ensures that the most accurate and up-to-date information is retained in the customer profile. Reference = Configure Merge Rules Based on Data Quality | SAP Help Portal, Merge Rules | SAP Help Portal In the context of the SAP Customer Data Platform, defining merge rules at the attribute level is crucial for managing how incoming data is integrated with existing customer profiles. Two significant rules that must be specified at this level include:
A . Decide whether to concatenate the incoming value with the existing value of the same attribute: This rule determines how to handle scenarios where an incoming data value for a specific attribute should be added to the existing value(s) for that attribute in the profile, rather than replacing it. Concatenation can be useful for attributes where maintaining a history or collection of values is important, such as addresses or phone numbers.
D . Decide whether to override existing data, based on the quality of the incoming and existing data: This rule involves assessing the quality or reliability of incoming data compared to what is already present in the customer profile and deciding whether the new data should replace the old. This could be based on factors like data source credibility, recency, or completeness, ensuring that the customer profile remains as accurate and up-to-date as possible.
These rules are integral to maintaining the integrity and usefulness of customer data within the platform, ensuring that data merging and updating processes are carried out in a way that enhances the quality of the customer profiles.

NEW QUESTION # 35
......

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