C-BW4H-2404通過考試 & C-BW4H-2404最新考古題

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SAP C-BW4H-2404 考試大綱：

主題	簡介
主題 1	Data Modeling and Design: This segment delves into the attributes and features of modeling entities within SAP BW 4HANA and SAP HANA HDI frameworks.
主題 2	SAP BW 4HANA Project and the Modeling Process: This segment offers direction on orchestrating SAP BW 4HANA initiatives.
主題 3	Fundamentals: This portion explores key terminologies, principles, and benefits of SAP BW 4HANA built on SAP HANA technology.
主題 4	SAP Datasphere: This part investigates the implementation of SAP Datasphere, encompassing its modeling components and the SAP BW bridge capabilities.

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最新的 SAP Certified Associate C-BW4H-2404 免費考試真題 (Q71-Q76):

問題 #71
"What are benefits of separating master data from transactional data in SAP BW/4HANA? Note: There are 3 correct answer to this question."

A. Allowing different data load frequency
B. Providing language dependent master data texts.
C. Reducing the number of data transfer processes
D. Ensuring referential integrity on your transactional data
E. Avoiding generation of SID values.

答案：A,B,D

解題說明：
Separating master data from transactional data in SAP BW/4HANA has the following benefits:
It allows different data load frequency for master data and transactional data, which can improve the performance and flexibility of data loading processes. For example, master data can be loaded daily or weekly, while transactional data can be loaded hourly or near real-time.
It ensures referential integrity on your transactional data by using SID values that link the transactional data to the master data. This way, the transactional data can be consistent and accurate across different InfoProviders and queries.
It provides language dependent master data texts that can be displayed in different languages according to the user's preference. This way, the master data can be more user-friendly and understandable for different audiences.

問題 #72
Why should you run an SAP HANA delta merge? Note: There are 2 correct answers to this question.

A. To combine the query cache from different executions
B. To move the most recent data from disk to memory
C. To decrease memory consumption
D. To improve the read performance of InfoProviders

答案：C,D

問題 #73
For which scenarios do you use the SAP HANA model focus? Note: There are 2 correct answers to this question.

A. Build views procedures using SQL script.
B. Define calculations using geospatial functions.
C. Load snapshots using ABAP CDS Views.
D. Define ABAP Managed Database Procedures in data flows.

答案：A,D

解題說明：
B. Build views procedures using SQL script:
* This is a core feature of SAP HANA modeling, where you can define Calculation Views or Procedures directly using SQL scripts for advanced data transformations and calculations.

問題 #74
What are prerequisites for S-API Extractors to load data directly into SAP Datasphere core tenant using delta mode? Note: There are 2 correct answers to this question.

A. A primary key needs to exist.
B. Operational Data Provisioning (ODP) must be enabled
C. Real-time access needs to be enabled
D. Extractor must be based on a function module

答案：A,C

問題 #75
You create an SAP HANA HDI Calculation View.
What are some of the reasons to choose the data category Cube with Star Join instead of data category Dimension? Note: There are 3 correct answers to this question.

A. You can persist transactional data.
B. You can create restricted columns.
C. You can provide default time characteristics.
D. You can combine master data transactional data.
E. You can aggregate measures as a sum.

答案：C,D,E

解題說明：
When creating an SAP HANA HDI Calculation View, choosing thedata category Cube with Star JoinoverDimensiondepends on the specific requirements of your data model. Below is a detailed explanation of why the verified answers are correct.
* Data Category Dimension:
* Used for modeling master data or reference data.
* Does not support measures or aggregations.
* Typically used for descriptive attributes (e.g., customer names, product descriptions).
* Data Category Cube with Star Join:
* Used for modeling transactional data with measures and dimensions.
* Supports star schema designs, combining fact tables (measures) and dimension tables (attributes).
* Enables advanced features like aggregations, time characteristics, and joins between master and transactional data.
* Star Join:
* A star join connects a fact table (containing measures) with dimension tables (containing attributes) in a star schema.
* It is optimized for performance and scalability in analytical queries.
Key Concepts:
* Option A: You can combine master data transactional data.
* Why Correct?The Cube with Star Join data category is specifically designed to combine transactional data (fact tables) with master data (dimension tables). This enables comprehensive reporting and analysis.
* Option B: You can persist transactional data.
* Why Incorrect?Persisting transactional data is not a feature of the Cube with Star Join data category. Persistence is typically handled at the database or application layer.
* Option C: You can provide default time characteristics.
* Why Correct?The Cube with Star Join data category supports default time characteristics (e.g., fiscal year, calendar year), which are essential for time-based reporting and analysis.
* Option D: You can create restricted columns.
* Why Incorrect?Restricted columns are a feature of calculation views but are not specific to the Cube with Star Join data category. They can also be created in Dimension views.
* Option E: You can aggregate measures as a sum.
* Why Correct?The Cube with Star Join data category supports aggregations, such as summing measures. This is a key feature for analyzing transactional data.
Verified Answer Explanation:
* SAP HANA Modeling Guide:The guide explains the differences between data categories like Dimension and Cube with Star Join, highlighting their respective use cases.
* SAP Note 2700850:This note provides examples of scenarios where Cube with Star Join is preferred over Dimension, emphasizing its ability to handle transactional data and aggregations.
* SAP Best Practices for HANA Modeling:SAP recommends using Cube with Star Join for analytical models that require combining master and transactional data, providing default time characteristics, and performing aggregations.

問題 #76
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