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GoShikenのSAPのC_BCBDC_2505試験トレーニング資料はIT認証試験を受ける全ての受験生が試験に合格することを助けるもので、受験生からの良い評価をたくさんもらいました。GoShikenを選ぶのは成功を選ぶのに等しいです。もしGoShikenのSAPのC_BCBDC_2505試験トレーニング資料を購入した後、学習教材は問題があれば、或いは試験に不合格になる場合は、私たちが全額返金することを保証いたしますし、私たちは一年間で無料更新サービスを提供することもできます。
SAP C_BCBDC_2505 認定試験の出題範囲:
トピック
出題範囲
トピック 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.
トピック 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.
トピック 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.
SAP Certified Associate - SAP Business Data Cloud 認定 C_BCBDC_2505 試験問題 (Q11-Q16):
質問 # 11
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 data provisioning adapter is installed.
- B. The DP Agent is configured for a dedicated space in SAP Datasphere.
- C. The Cloud Connector is installed on a local host.
- D. The DP Agent is installed and configured on a local host.
正解:A、D
解説:
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.
質問 # 12
Which of the following can you do with an SAP Datasphere Data Flow? Note: There are 3 correct answers to this question.
- A. Fill different target tables in parallel.
- B. Write data to a table in a different SAP Datasphere tenant.
- C. Integrate data from different sources into one table.
- D. Use a Python script for data transformation.
- E. Delete records from a target table.
正解:A、C、D
解説:
An SAP Datasphere Data Flow is a highly versatile and powerful tool for data integration, transformation, and loading. With a Data Flow, you can effectively integrate data from different sources into one table (B). This is a fundamental capability, allowing you to combine data from various tables, views, or even external connections, apply transformations, and consolidate it into a single target table. Another advanced capability is to fill different target tables in parallel (D). Data Flows are designed to handle complex scenarios efficiently, and this parallelism optimizes performance when you need to populate multiple destination tables simultaneously from a single flow. Furthermore, Data Flows support extensibility, allowing you to use a Python script for data transformation (E). This enables advanced, custom data manipulation logic that might not be available through standard graphical operations, providing immense flexibility for complex business rules. Writing data to a different Datasphere tenant (A) is not a direct capability of a Data Flow, and deleting records from a target table (C) is typically handled via specific operations within the target table's management or through SQL scripts rather than a standard data flow write operation.
質問 # 13
Which of the following options will duplicate data to SAP HANA cloud under SAP Datasphere, based on data from an external source object?
There are 3 correct answers to this question.
Response:
- A. Create a graphical view based on a remote table for that source object and persist the view data
- B. Import a source as a remote table without taking any further action
- C. Use a data flow to fill a target table
- D. Import a source as a remote table and schedule replication
- E. Use a replication flow to fill a local table
正解:C、D、E
質問 # 14
What do you use to write data from a local table in SAP Datasphere to an outbound target?
- A. CSN Export
- B. Replication Flow
- C. Transformation Flow
- D. Data Flow
正解:D
解説:
To write data from a local table in SAP Datasphere to an outbound target, you primarily use a Data Flow. A Data Flow in SAP Datasphere is a powerful tool designed for comprehensive data integration and transformation. It allows you to extract data from various sources (including local tables within Datasphere), perform various transformations (like joins, aggregations, filtering, scripting), and then load the processed data into a specified target. This target can be another local table, a remote table, or an outbound target like an external database or a file system. While a Replication Flow (C) is used for ingesting data into Datasphere, and a Transformation Flow (A) is not a standalone artifact for outbound writes (often part of a Data Flow), the Data Flow provides the complete framework for extracting, transforming, and loading data, including sending it to external destinations.
質問 # 15
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 persisted by using real-time replication.
- B. Data can be persisted in SAP Datasphere by creating a snapshot (copy of data).
- C. Data access can be switched from virtual to persisted, but not the other way around.
- D. Data can be accessed virtually by remote access to the source system.
- E. Data can be loaded using advanced transformation capabilities.
正解:A、B、D
解説:
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.
質問 # 16
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