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Verified SAP Certification C_BCBDC_2505 Test Questions & The Best ITexamReview - Leader in Certification Exam Materials

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SAP C_BCBDC_2505 Exam Syllabus Topics:

TopicDetails
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 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.
Topic 3
  • 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.

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SAP Certified Associate - SAP Business Data Cloud Sample Questions (Q74-Q79):

NEW QUESTION # 74
What are some features of the out-of-the-box reporting with intelligent applications in SAP Business Data Cloud? Note: There are 2 correct answers to this question.

  • A. Automated data provisioning from business application to dashboard
  • B. Manual creation of artifacts across all involved components
  • C. AI-based suggestions for intelligent applications in the SAP Business Data Cloud Cockpit
  • D. Services for transforming and enriching data

Answer: A,D

Explanation:
The out-of-the-box reporting capabilities with intelligent applications in SAP Business Data Cloud (BDC) are designed to streamline the analytical process and deliver immediate value. Two significant features include automated data provisioning from business application to dashboard. This means that intelligent applications handle the end-to-end flow of data, from its source in operational systems, through processing in BDC, and finally to visualization in dashboards, with minimal manual intervention. This automation ensures timely and consistent data delivery for reporting. Additionally, these intelligent applications leverage services for transforming and enriching data. As part of the pre-built logic within these applications, data is automatically transformed (e.g., aggregated, filtered) and enriched (e.g., adding calculated KPIs, combining with master data) to make it immediately suitable for reporting and analysis. This reduces the need for manual data manipulation by users, providing ready-to-consume insights.


NEW QUESTION # 75
For a model in SAP Analytics Cloud you are using a live connection. Where is the data stored?

  • A. Source system
  • B. Public dataset
  • C. Embedded dataset
  • D. SAP Analytics Cloud model

Answer: A

Explanation:
When an SAP Analytics Cloud (SAC) model utilizes a live connection, the data is not stored within SAP Analytics Cloud itself. Instead, the data resides entirely in the source system. This means that SAC directly queries the data from the connected system (e.g., SAP HANA, SAP BW, SAP S/4HANA, or SAP Datasphere) in real-time every time a user interacts with the story or application. Only metadata, such as dimension definitions and measure aggregations, is stored in SAC. This approach offers several significant advantages: it ensures that users always work with the most current data, eliminates the need for data replication, and often addresses data privacy and security concerns by keeping sensitive data within the customer's secure landscape. The "live" nature means that any changes in the source system are immediately reflected in SAC.


NEW QUESTION # 76
What is required to use version management in an SAP Analytics Cloud story?

  • A. Classic mode
  • B. Planning model
  • C. Optimized mode
  • D. Analytic model

Answer: B

Explanation:
To leverage version management capabilities within an SAP Analytics Cloud (SAC) story, it is a fundamental requirement that the story is built on a planning model. Version management is a core feature specifically designed for planning functionalities. It enables users to create, manage, and compare different scenarios or iterations of data, such as "Actual," "Budget," "Forecast," or various planning versions. This is critical for budgeting, forecasting, and what-if analysis, allowing planners to work on different data sets concurrently and track changes over time. While analytic models are used for general reporting and analysis, they do not inherently support the robust version management features that are integral to planning processes. Therefore, if you intend to utilize version management to compare different data scenarios or manage planning cycles, your SAC story must be connected to a planning model.


NEW QUESTION # 77
Which of the following are features of SAP Business Data Cloud's data integration capabilities?
There are 2 correct answers to this question.
Response:

  • A. Email data import
  • B. Manual data entry forms
  • C. Real-time data replication
  • D. Batch data processing

Answer: C,D


NEW QUESTION # 78
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 # 79
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