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SAP C_BCBDC_2505 Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 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 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.

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SAP Certified Associate - SAP Business Data Cloud Sample Questions (Q51-Q56):NEW QUESTION # 51
Which options do you have when using the remote table feature in SAP Datasphere? Note: There are 3 correct answers to this question.
Answer: A,D,E
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 # 52
What is required to use version management in an SAP Analytics Cloud story?
Answer: A
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 # 53
What are some use cases for an SAP Datasphere task chain? Note: There are 3 correct answers to this question.
Answer: A,B,C
Explanation:
SAP Datasphere task chains are powerful tools for orchestrating and automating sequences of operations, making them ideal for managing complex data pipelines and recurring processes. One key use case is to Create or Refresh View Persistency (A). If you have views for which you want to persist the data (materialize them into tables) for performance or specific analytical needs, a task chain can automate the scheduled recreation or refresh of these persistent views. Another common use case is to Execute a Replication Flow and Transformation Flow in sequence (C). This allows you to define a process where data is first replicated from a source system into Datasphere, and then immediately followed by transformation steps to cleanse, enrich, or aggregate that data, ensuring a fully automated end-to-end data preparation. Furthermore, task chains can be used to Run an Open SQL Schema Procedure (D). This provides flexibility to integrate custom SQL logic or stored procedures into an automated workflow, enabling advanced data manipulation or administrative tasks. Uploading a CSV file (B) is typically a manual import action, and executing a data action for a planning function (E) relates to planning models, not general Datasphere task chains.

NEW QUESTION # 54
What is the main storage type of the object store in SAP Business Data Cloud?
Answer: A
Explanation:
The primary storage type for the object store within the SAP Business Data Cloud (BDC) architecture is SAP HANA data lake files. SAP BDC is designed to handle vast amounts of diverse data, including semi-structured and unstructured data, which is efficiently stored in a data lake. The SAP HANA data lake, specifically its file storage component, provides a highly scalable and cost-effective solution for retaining raw, historical, and detailed data. This contrasts with traditional relational databases (like SAP HANA extended tables) or data warehousing constructs (like BW/4HANA DataStore objects or InfoObjects), which are optimized for structured, aggregated data and specific query patterns. The object store's reliance on data lake files in BDC underscores its capability to manage enterprise-wide data regardless of its structure, making it suitable for a wide range of analytical workloads, including those involving machine learning and advanced analytics where raw data access is crucial.

NEW QUESTION # 55
What is the role of "Spaces" in SAP Business Data Cloud?
Please choose the correct answer.
Response:
Answer: B

NEW QUESTION # 56
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