Quiz Authoritative C_BW4H_2404 - New SAP Certified Associate - Data Engineer - Data Fabric Dumps Ppt
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SAP Certified Associate - Data Engineer - Data Fabric Sample Questions (Q51-Q56):
NEW QUESTION # 51
What are the prerequisites for deleting business partner attribute master data in SAP BW/4HANA? Note:
There are 2 correct answers to this question.
Answer: A,B
Explanation:
B. No hierarchy data related to business partner values:
* Hierarchical relationships in SAP BW/4HANA must not reference the business partner values being deleted. These relationships are maintained at runtime and prevent deletion if still active.
C. No transaction data referring to business partner values:
* Transactional dependencies must be cleared before deleting master data, as references in advanced DataStore Objects would cause inconsistency.
References:SAP BW/4HANA Master Data Deletion documentation (SAP Help Portal).
NEW QUESTION # 52
Which join types can you use in a Composite Provider? Note: There are 3 correct answers to this question.
Answer: B,C,E
Explanation:
C. Full Outer Join:
* Combines data from both sources, including unmatched rows from either side.
D. Referential Join:
* Optimized join that assumes data consistency between the sources for faster query performance.
E. Inner Join:
* Only combines rows with matching keys in both sources, commonly used for exact matches.
References:SAP BW/4HANA Composite Provider documentation (SAP Help Portal).
NEW QUESTION # 53
Which feature of a DataStore object (advanced) should be made available to improve the performance for data analysis?
Answer: C
Explanation:
* DataStore Object (Advanced): In SAP BW/4HANA, a DataStore Object (advanced) is a flexible data storage object that supports both staging and reporting. It allows for detailed data storage and provides advanced features like partitioning, compression, and snapshot support.
* Partitioning: Partitioning divides large datasets into smaller, manageable chunks based on specific criteria (e.g., time-based or value-based). This improves query performance by reducing the amount of data scanned during analysis.
* Snapshot Support: This feature allows periodic snapshots of data to be stored in the DataStore Object (advanced). While useful for historical analysis, it does not directly improve query performance.
* Inventory Management: This is unrelated to performance optimization in the context of data analysis.
* ChangeLog: The ChangeLog stores delta records for incremental updates. While important for data loading, it does not directly enhance query performance.
Key Concepts:Why Partitioning Improves Performance:Partitioning is a well-known technique in database management systems to optimize query performance. By dividing the data into partitions, queries can focus on specific subsets of data rather than scanning the entire dataset. For example:
* Time-based partitioning (e.g., by year or month) allows queries to target only relevant time periods.
* Value-based partitioning (e.g., by region or category) enables faster filtering of data.
In SAP BW/4HANA, enabling partitioning for a DataStore Object (advanced) significantly enhances the performance of data analysis by reducing I/O operations and improving parallel processing capabilities.
* A. Snapshot Support: While useful for historical reporting, it does not directly improve query performance.
* C. Inventory Management: This is unrelated to query performance and pertains to managing materialized data.
* D. ChangeLog: This is used for delta handling and does not impact query performance.
* SAP BW/4HANA Documentation: The official documentation highlights partitioning as a key feature for optimizing query performance in DataStore Objects (advanced).
* SAP Best Practices for Performance Optimization: Partitioning is recommended for large datasets to improve query execution times.
* SAP Note on DataStore Object (Advanced): Notes such as 2708497 discuss the benefits of partitioning for performance.
Why Other Options Are Incorrect:References:By enabling partitioning, you can significantly improve the performance of data analysis in a DataStore Object (advanced).
NEW QUESTION # 54
You create a Data Store object (advanced) using the "Data Mart DataStore Object" modeling property. Which behaviors are specific to this modeling property? Note: There are 2 correct answers to this question.
Answer: A,D
Explanation:
* Data Mart DataStore Object Properties:
* Designed for flexible reporting scenarios where data is treated with minimal restrictions.
* Key Behaviors:
* Union for Reporting (Answer C):Combines inbound and active tables for reporting, allowing real-time insights.
* Key Handling (Answer D):All characteristics are treated as part of the key, ensuring no duplicate records in the Data Mart.
* Change Log Activation (Option A):The change log is irrelevant for Data Mart DSOs.
* Query Results (Option B):Query results can be shown even before data activation.
Incorrect Options:References:
* SAP BW/4HANA Advanced DataStore Object Documentation
* SAP Data Mart Modeling Guide
NEW QUESTION # 55
What foundation is necessary to use SAP S/4HANA embedded analytics?
Answer: C
NEW QUESTION # 56
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