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SAP C_C4H63_2411 Exam Syllabus Topics:

Topic
Details

Topic 1

SAP Customer Data Platform: SAP Customer Data Solutions Consultants are expected to demonstrate comprehensive knowledge of the SAP Customer Data Platform. This domain covers the platform's core functionalities, including data collection, unification, and activation.

Topic 2

Implementing B2B: In this final section, the main focus is on implementing SAP Customer Data Solutions in business-to-business (B2B) contexts. SAP Customer Data Solutions Consultants should understand the unique challenges and requirements of B2B customer data management.

Topic 3

Data Ingestion: Data ingestion is a core component of customer data platforms, and assesses the consultant's expertise in this area. It covers various methods and tools for importing data from multiple sources into the SAP Customer Data Platform.

Topic 4

Managing Clean Core: This section of the exam measures the skills of SAP Customer Data Solutions Consultants and covers the management of Clean Core in SAP systems. It comprises understanding the principles of maintaining a clean core, which involves keeping the central system free from custom modifications. The exam may assess the ability to implement clean core strategies effectively while ensuring system integrity and performance.

Topic 5

Data Activation: This module of the exam, focuses on the activation of customer data for various business purposes. SAP Customer Data Solutions Consultants should understand how to leverage unified customer profiles for marketing, sales, and service activities.

Topic 6

APIs: This section focuses on the use of APIs in the context of SAP Customer Data Solutions. It assesses the consultant's understanding of how to integrate and leverage APIs for data exchange and system interoperability.

Topic 7

Insights: The Insights section of the exam evaluates the consultant's ability to extract meaningful insights from customer data. It covers analytics capabilities within the SAP Customer Data Platform and how to use them effectively. Candidates should be able to create and interpret various types of reports and dashboards.

Topic 8

Data Privacy: This section focuses on data privacy considerations in customer data management. SAP Customer Data Solutions Consultants should be well-versed in data protection regulations and privacy-enhancing technologies. The exam may evaluate the ability to implement privacy-compliant data handling processes and ensure adherence to relevant laws and standards.

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SAP Certified Associate - Implementation Consultant - SAP Customer Data Platform Sample Questions (Q56-Q61):

NEW QUESTION # 56
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 what to do if a data conflict occurs for an identifier attribute
C. Decide whether to override existing data, based on the quality of the incoming and existing data
D. Decide whether more than one value can be saved for an attribute

Answer: A,C

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 # 57
What are some valid use cases for audience activation? Note: There are 3 correct answers to this question.

A. Run targeted email campaigns based on customer activities and preferences.
B. Merge incoming customer data from ERP back end.
C. Run marketing campaigns on social media platforms.
D. Import customer contacts from CRM systems.
E. Update customer loyalty level in a loyalty system.

Answer: A,C,E

Explanation:
Valid use cases for audience activation within the SAP Customer Data Platform include:
Running marketing campaigns on social media platforms: Marketers can activate audiences to export data into external applications like social media platforms to run marketing campaigns1.
Running targeted email campaigns based on customer activities and preferences: Audiences can be used to run targeted email campaigns that are based on customer actions and choices1.
Updating customer loyalty level in a loyalty system: While not explicitly stated in the provided resources, updating customer loyalty levels is a common use case for audience activation, as it involves using customer data to personalize and improve customer experience.
Reference = The use cases are supported by the SAP Customer Data Platform's learning resources, which detail the process of creating audiences and the purposes for which they can be activated12.

NEW QUESTION # 58
You are using predictive indicators to configure predictive models and view results. What types of models can you design? Note: There are 3 correct answers to this question.

A. Predict events for groups
B. Predict customer lifetime value for profiles
C. Predict chum probabilities for profiles
D. Predict actions for groups
E. Predict churn probabilities for groups

Answer: B,C,E

Explanation:
Within the SAP Customer Data Platform, you can design predictive models, also known as predictive indicators, for various purposes. The types of models you can create include predicting churn probabilities for individual profiles (CHURN Profile), predicting churn probabilities for groups (CHURN Group), and predicting customer lifetime value for individual profiles (CLV Profile). These models help in understanding and anticipating customer behaviors, which is crucial for maintaining customer relationships and maximizing customer value.
Reference = The types of predictive models available for configuration in the SAP Customer Data Platform are detailed in the SAP Help Portal documentation on managing models and predictive indicators1.

NEW QUESTION # 59
How can you obtain the application key and secret for authorization of REST API calls to SAP Customer Data Platform?

A. By creating a server application from the application library
B. By copying the authorization key and secret from the event listener
C. By configuring the connector in the Connector Studio
D. By creating a ticket in SAP for Me

Answer: A

NEW QUESTION # 60
There are four key stages or steps overarching the SAP Customer Data Platform.
Besides Data Ingestion, what are the other three stages or steps?
Note: There are 3 correct answers to this question.

A. Optimization
B. Identity Resolution
C. Transformation
D. Data Insights
E. Engagement

Answer: B,D,E

NEW QUESTION # 61
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