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These SAP Certified Associate - Data Engineer - Data Fabric (C_BW4H_2404) practice test covers all the topics of the C_BW4H_2404 test and includes real C_BW4H_2404 questions. If you are attempting the C_BW4H_2404 examination for the first time, you will get an exact idea about the C_BW4H_2404 exam and how you can clear it with flying colors. These SAP C_BW4H_2404 Questions are available in desktop C_BW4H_2404 practice exam software, web-based C_BW4H_2404 practice test, and SAP Certified Associate - Data Engineer - Data Fabric (C_BW4H_2404) dumps pdf format.
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NEW QUESTION # 15
Which tasks require access to the BW bridge cockpit? Note: There are 2 correct answers to this question.
Answer: B,C
Explanation:
* Software Component Setup (Answer B):
* The BW bridge cockpit facilitates managing the configuration and setup of necessary software components for integration.
* Communication Systems (Answer D):
* The cockpit is used to establish communication systems for connecting BW bridge and external systems.
* Transport Requests (Option A):Transport requests are managed outside the cockpit in standard SAP tools.
* Source Systems (Option C):Source system setup is done in the SAP BW/4HANA system or Datasphere configuration.
Incorrect Options:References:
* SAP BW Bridge Cockpit Documentation
* SAP Datasphere Integration Guide
NEW QUESTION # 16
Which are purposes of the Open Operational Data Store layer in the layered scalable architecture (LSA++) of SAP BW/4HANA? Note: There are 2 correct answers to this question.
Answer: A,B
NEW QUESTION # 17
For which reasons should you run an SAP HANA delta merge? Note: There are 2 correct answers to this question.
Answer: B,D
Explanation:
In SAP HANA, thedelta mergeoperation is a critical process for managing data storage and optimizing query performance. It is particularly relevant in columnar storage systems like SAP HANA, where data is stored in two parts: themain storage(optimized for read operations) and thedelta storage(optimized for write operations). The delta merge operation moves data from the delta storage to the main storage, ensuring efficient data management and improved query performance.
* To Decrease Memory Consumption (A):The delta storage holds recent changes (inserts, updates, deletes) in a row-based format, which is less memory-efficient compared to the columnar format used in the main storage. Over time, as more data accumulates in the delta storage, it can lead to increased memory usage. Running a delta merge moves this data into the main storage, which is compressed and optimized for columnar storage, thereby reducing overall memory consumption.
* To Improve the Read Performance of InfoProviders (D):Queries executed on SAP HANA tables or InfoProviders (such as ADSOs, CompositeProviders, or BW queries) benefit significantly from data being stored in the main storage. The main storage is optimized for read operations due to its columnar structure and compression techniques. When data resides in the delta storage, queries must access both the delta and main storage, which can degrade performance. By running a delta merge, all data is consolidated into the main storage, improving read performance for reporting and analytics.
Why Run an SAP HANA Delta Merge?
* To Combine the Query Cache from Different Executions (B):This is incorrect because the delta merge operation does not involve the query cache. The query cache in SAP HANA is a separate mechanism that stores results of previously executed queries to speed up subsequent executions. The delta merge focuses solely on moving data between delta and main storage and does not interact with the query cache.
* To Move the Most Recent Data from Disk to Memory (C):This is incorrect because SAP HANA's in- memory architecture ensures that all data, including the most recent data, is already stored in memory.
The delta merge operation does not move data from disk to memory; instead, it reorganizes data within memory (from delta to main storage). Disk storage in SAP HANA is typically used for persistence and backup purposes, not for active query processing.
Incorrect Options:
SAP Data Engineer - Data Fabric Context:In the context ofSAP Data Engineer - Data Fabric, understanding the delta merge process is essential for optimizing data models and ensuring high-performance analytics. SAP HANA is often used as the underlying database for SAP BW/4HANA and other data fabric solutions. Efficient data management practices, such as scheduling delta merges, contribute to seamless data integration and transformation across the data fabric landscape.
For further details, you can refer to the following resources:
* SAP HANA Administration Guide: Explains the delta merge process and its impact on system performance.
* SAP BW/4HANA Documentation: Discusses how delta merges affect InfoProvider performance in BW queries.
* SAP Learning Hub: Provides training materials on SAP HANA database administration and optimization techniques.
By selectingA (To decrease memory consumption)andD (To improve the read performance of InfoProviders), you ensure that your SAP HANA system operates efficiently, with reduced memory usage and faster query execution.
NEW QUESTION # 18
What should you consider when you set the High Cardinality flag for a characteristic? Note: There are 2 correct answers to this question.
Answer: B,C
Explanation:
InSAP BW/4HANA, theHigh Cardinalityflag is used to optimize the handling of characteristics with a very large number of distinct values (e.g., transaction IDs, timestamps). However, enabling this flag imposes certain restrictions on how the characteristic can be used. Below is an explanation of the correct answers and why they are valid.
* A. You cannot use this characteristic as a navigation attribute for another characteristic.
* When theHigh Cardinalityflag is set, the characteristic cannot serve as anavigation attributefor another characteristic. Navigation attributes are used to provide additional descriptive information for a characteristic, but high-cardinality characteristics are not suitable for this purpose due to their large size and potential performance impact.
NEW QUESTION # 19
Which types of values can be protected by analysis authorizations? Note: There are 2 correct answers to this question.
Answer: B,C
NEW QUESTION # 20
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