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SAP C_BCBDC_2505 Exam Syllabus Topics:

Topic
Details

Topic 1

• SAP Business Data Cloud: This section of the exam measures the skills of Data Analysts and covers core concepts of the SAP Business Data Cloud. Candidates are expected to understand its key components, integration mechanisms, and how it functions as a foundation for unified data management across SAP and non-SAP environments. The focus is on enabling data connectivity and providing governed access to data across the enterprise.

Topic 2

• SAP Analytics Cloud: This section of the exam measures the skills of Data Analysts and covers the use of SAP Analytics Cloud in data visualization, story building, and dashboard creation. Candidates should be familiar with its planning and predictive capabilities, along with how to utilize data insights to drive business decision-making. It also includes managing user access and collaborating through shared analytics assets.

Topic 3

• SAP Datasphere: This section of the exam measures the skills of Solution Consultants and covers a comprehensive understanding of SAP Datasphere. Candidates should demonstrate knowledge of data modeling, transformation, and harmonization using SAP Datasphere tools. It evaluates how well they can work with data layer structuring, semantic modeling, and integration to support real-time data access for various business applications.

 

SAP Certified Associate - SAP Business Data Cloud Sample Questions (Q32-Q37):

NEW QUESTION # 32
Which operation is implemented by the Foundation Services of SAP Business Data Cloud?

• A. Execution of machine learning algorithms to generate additional insights.
• B. Generation of an analytic model by adding semantic information.
• C. Data transformation and enrichment to generate a data product.
• D. Storage of raw data inside a CDS view.

Answer: C

Explanation:
The Foundation Services component of SAP Business Data Cloud (BDC) is responsible for orchestrating the fundamental processes of data preparation and productization. Specifically, a key operation implemented by Foundation Services is data transformation and enrichment to generate a data product. Foundation Services takes raw data ingested from various business applications and applies necessary transformations, cleanses it, and enriches it with additional context or calculated attributes. This process is crucial for creating high-quality, consumable data products, which are curated and semantically rich datasets designed for specific business use cases. While machine learning algorithms are executed by Intelligent Applications (which consume these data products), and analytic models are built in SAP Datasphere (which is part of the BDC ecosystem), Foundation Services focuses on the foundational work of preparing and productizing the data itself, ensuring it's ready for advanced analytics and consumption.

 

NEW QUESTION # 33
How can you create a local table with a custom name in SAP Datasphere? Note: There are 2 correct answers to this question.

• A. By creating a persistent snapshot of a view
• B. By creating an intelligent lookup
• C. By adding an output of a data flow
• D. By importing a CSV file

Answer: C,D

Explanation:
In SAP Datasphere, there are several ways to create a local table with a custom name, providing flexibility for data management. Two common methods are by importing a CSV file and by adding an output of a data flow. When you import a CSV file, Datasphere allows you to specify a custom name for the new local table that will store the imported data. This is a quick and straightforward way to bring external, flat-file data into Datasphere. Secondly, a data flow in Datasphere allows you to define a sequence of operations (e.g., transformations, aggregations) and write the processed data to a target. When configuring the output of a data flow, you can specify a new local table and provide it with a custom name. This method is ideal for creating structured tables as a result of complex data integration or transformation processes. These options ensure that users can create and name tables according to their specific data modeling and organizational requirements.

 

NEW QUESTION # 34
A company wants to enable self-service data access for analysts while maintaining centralized control over source data. Which SAP Business Data Cloud capabilities help meet these requirements?
There are 3 correct answers to this question.
Response:

• A. Exporting data to Excel for distribution
• B. Business Builder for semantic modeling
• C. Remote table access to avoid duplication
• D. Data replication via CSV uploads
• E. Role-based access management

Answer: B,C,E

 

NEW QUESTION # 35
What is the role of SAP Databricks in SAP Business Data Cloud?
Please choose the correct answer.
Response:

• A. To enhance intelligent applications by adding planning functions
• B. To provide a graphical interface for the business user who will develop data models
• C. To enrich data products with Al and machine learning
• D. To integrate ABAP function modules for data type conversions in SAP-based data sources

Answer: C

 

NEW QUESTION # 36
Which options do you have when using the remote table feature in SAP Datasphere? Note: There are 3 correct answers to this question.

• A. Data can be persisted by using real-time replication.
• B. Data can be accessed virtually by remote access to the source system.
• C. Data can be persisted in SAP Datasphere by creating a snapshot (copy of data).
• D. Data can be loaded using advanced transformation capabilities.
• E. Data access can be switched from virtual to persisted, but not the other way around.

Answer: A,B,C

Explanation:
The remote table feature in SAP Datasphere offers significant flexibility in how data from external sources is consumed and managed. Firstly, data can be accessed virtually by remote access to the source system (E). This means Datasphere does not store a copy of the data; instead, it queries the source system in real-time when the data is requested. This ensures that users always work with the freshest data. Secondly, data can be persisted in SAP Datasphere by creating a snapshot (copy of data) (C). This allows users to explicitly load a copy of the remote table's data into Datasphere at a specific point in time, useful for performance or offline analysis. Lastly, data can be persisted by using real-time replication (D). For certain source systems and configurations, Datasphere supports continuous, real-time replication, ensuring that changes in the source system are immediately reflected in the persisted copy within Datasphere. Option A is incorrect as the access mode cannot be arbitrarily switched, and option B refers to data flow capabilities, not inherent remote table access options.

 

NEW QUESTION # 37
......

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