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[General] C_BCBDC_2505 Reliable Test Sample, C_BCBDC_2505 Practice Guide

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【General】 C_BCBDC_2505 Reliable Test Sample, C_BCBDC_2505 Practice Guide

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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 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.

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SAP Certified Associate - SAP Business Data Cloud Sample Questions (Q29-Q34):NEW QUESTION # 29
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. Data replication via CSV uploads
  • B. Role-based access management
  • C. Business Builder for semantic modeling
  • D. Remote table access to avoid duplication
  • E. Exporting data to Excel for distribution
Answer: B,C,D

NEW QUESTION # 30
What are some use cases for an SAP Datasphere task chain? Note: There are 3 correct answers to this question.
  • A. Execute a data action for a planning function
  • B. Upload a CSV file into a local table
  • C. Create or Refresh View Persistency
  • D. Execute a Replication Flow and Transformation Flow in sequence
  • E. Run an Open SQL Schema Procedure
Answer: C,D,E
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 # 31
What are the data sources for Data Analyzer?
Please select all the correct answers that apply.
Response:
  • A. SAP HANA Live Views
  • B. Microsoft Excel files
  • C. SAP Analytics Cloud Models
  • D. SAP BW Queries
  • E. CSV files
  • F. SAP Datasphere
Answer: A,C,D,F

NEW QUESTION # 32
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 loaded using advanced transformation capabilities.
  • B. Data can be accessed virtually by remote access to the source system.
  • C. Data access can be switched from virtual to persisted, but not the other way around.
  • D. Data can be persisted by using real-time replication.
  • E. Data can be persisted in SAP Datasphere by creating a snapshot (copy of data).
Answer: B,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 # 33
Which of the following data source objects can be used for an SAP Datasphere Replication Flow? Note: There are 2 correct answers to this question.
  • A. Google Big Query dataset
  • B. ABAP CDS view
  • C. MS Azure SQL table
  • D. Oracle database table
Answer: B,D
Explanation:
SAP Datasphere Replication Flows are designed for efficient and continuous data transfer from source systems into Datasphere. For these flows, specific types of data source objects are supported to ensure robust and reliable replication. Two common and highly supported data source objects are an ABAP CDS view (Core Data Services view) and an Oracle database table. ABAP CDS views are particularly relevant for replicating data from SAP source systems (like SAP S/4HANA or SAP ERP), as they provide a semantically rich and optimized way to access business data. Oracle database tables represent a broad category of third-party relational databases from which data can be replicated. While Datasphere offers connectivity to various cloud data warehouses like Google BigQuery or MS Azure SQL for virtual access or snapshotting, Replication Flows are typically used for continuous, high-volume data ingestion from operational databases and SAP systems using their native database tables or views like CDS views.

NEW QUESTION # 34
......
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