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  1. Home
  2. SAP Certification
  3. C_BCBDC_2505 Exam
  4. SAP.C_BCBDC_2505.v2025-11-28.q35 Dumps
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Question 21

Why would you choose the "Validate Remote Tables" feature in the SAP Datasphere repository explorer?

Correct Answer: D
The "Validate Remote Tables" feature in the SAP Datasphere repository explorer is primarily used to identify structure updates of the remote sources. When a remote table is created in Datasphere, it establishes a metadata connection to a table or view in an external source system. Over time, the structure of the source object (e.g., column additions, deletions, data type changes) might change. The "Validate Remote Tables" function allows you to compare the metadata currently stored in Datasphere for the remote table with the actual, current metadata in the source system. If discrepancies are found, Datasphere can highlight these structural changes, prompting you to update the remote table's definition within Datasphere to match the source. This ensures that views and data flows built on these remote tables continue to function correctly and align with the underlying source structure, preventing data access issues or incorrect data interpretations.
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Question 22

You want to use the embedded help function in SAP Analytics Cloud to support you. What is offered by the embedded help?
There are 2 correct answers to this question.
Response:

Correct Answer: B,D
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Question 23

You want to combine external data with internal data via product ID. Although the data may be inconsistent, such as the external data contains the letter "O" where the internal data contains the digit 0, you still want to combine them. Which artifact should you use for matching?

Correct Answer: D
When faced with the challenge of combining data from different sources where the matching keys (like "Product ID") are inconsistent or contain variations (e.g., "O" vs. "0"), the recommended artifact in SAP Datasphere for such fuzzy or approximate matching scenarios is an Intelligent Lookup. An Intelligent Lookup (D) leverages machine learning capabilities to identify and map records that are semantically similar but not exact matches. Unlike standard joins in graphical views or SQL views which require precise key matches, Intelligent Lookups can handle data quality issues, typos, and variations, allowing you to successfully link disparate records that would otherwise be missed. This is particularly valuable when integrating data from external systems or legacy sources where perfect data standardization is not feasible, ensuring a more comprehensive and accurate combined dataset for analysis.
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Question 24

Related to data management, what are some capabilities of SAP Business Data Cloud? Note: There are 2 correct answers to this question.

Correct Answer: B,D
SAP Business Data Cloud (BDC) offers significant capabilities in data management, primarily focusing on creating a unified and actionable data foundation. Two key capabilities are to integrate and enrich customer business data for different analytics use cases. BDC pulls data from various SAP and non-SAP sources, allowing for consolidation and enhancement of this data to provide a comprehensive view for analytical purposes. This includes applying business context and semantic richness. Secondly, a critical capability is to harmonize customer business data across different Line of Business applications. BDC addresses the challenge of disparate data silos by creating a consistent data model and definitions across various operational systems (e.g., ERP, CRM, HR), ensuring that data is understood and used uniformly across the enterprise. While BDC leverages hyperscaler environments, "storing data" is a characteristic of its infrastructure, not a direct capability of data management provided by BDC itself. Delegating integration is an operational choice, not a core capability of the platform.
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Question 25

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.

Correct Answer: B,C
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.
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