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Updated Valid C-BCBDC-2505 Exam Test Offer You The Best Hot Spot Questions | SAP Certified Associate - SAP Business Data Cloud

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SAP C-BCBDC-2505 Exam Syllabus Topics:

Topic
Details

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 (Q57-Q62):

NEW QUESTION # 57
What elements make up the framework for viewing data in SAP Analytics Cloud?
There are 2 correct answers to this question.
Response:

A. Allocations
B. Properties
C. Dimensions
D. Measures

Answer: C,D

NEW QUESTION # 58
What are the prerequisites for loading data using Data Provisioning Agent (DP Agent) for SAP Datasphere? Note: There are 2 correct answers to this question.

A. The DP Agent is installed and configured on a local host.
B. The Cloud Connector is installed on a local host.
C. The DP Agent is configured for a dedicated space in SAP Datasphere.
D. The data provisioning adapter is installed.

Answer: A,D

Explanation:
To load data into SAP Datasphere using the Data Provisioning Agent (DP Agent), two crucial prerequisites must be met. Firstly, the DP Agent must be installed and configured on a local host (A). The DP Agent acts as a bridge between your on-premise data sources and SAP Datasphere in the cloud. It needs to be deployed on a server within your network that has access to the source systems you wish to connect. Secondly, the relevant data provisioning adapter must be installed (B) within the DP Agent framework. Adapters are specific software components that enable the DP Agent to connect to different types of source systems (e.g., SAP HANA, Oracle, Microsoft SQL Server, filesystems). Without the correct adapter, the DP Agent cannot communicate with and extract data from your chosen source. While the Cloud Connector (C) is often used for secure access to SAP backend systems in the cloud, it's not a direct prerequisite for the DP Agent itself for all data sources. Configuring the DP Agent for a specific space (D) is a step after the initial installation and adapter setup.

NEW QUESTION # 59
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. Services for transforming and enriching data
B. AI-based suggestions for intelligent applications in the SAP Business Data Cloud Cockpit
C. Automated data provisioning from business application to dashboard
D. Manual creation of artifacts across all involved components

Answer: A,C

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 # 60
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. Batch data processing
D. Real-time data replication

Answer: C,D

NEW QUESTION # 61
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?

A. Graphical View
B. Intelligent Lookup
C. Entity Relationship Model
D. Analytic Model

Answer: B

Explanation:
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.

NEW QUESTION # 62
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