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C-BW4H-2505 Exam Certification Cost - Visual C-BW4H-2505 Cert Exam

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SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q26-Q31):

NEW QUESTION # 26
Which type of data builder object can be used to fetch delta data from a remote table located in the SAP BW bridge space?

A. Replication Flow
B. Data Flow
C. Transformation Flow
D. Entity relationship model

Answer: A

Explanation:
* Delta Data: Delta data refers to incremental changes (inserts, updates, or deletes) in a dataset since the last extraction. Fetching delta data is essential for maintaining up-to-date information in a target system without reprocessing the entire dataset.
* SAP BW Bridge Space: The SAP BW bridge connects SAP BW/4HANA with SAP Datasphere, enabling real-time data replication and virtual access to remote tables.
* Data Builder Objects: In SAP Datasphere, Data Builder objects are used to define and manage data flows, transformations, and replications. These objects include Replication Flows, Transformation Flows, and Entity Relationship Models.
* A. Transformation Flow:A Transformation Flow is used to transform data during the loading process.
While useful for data enrichment or restructuring, it does not specifically fetch delta data from a remote table.
* B. Entity Relationship Model:An Entity Relationship Model defines the relationships between entities in SAP Datasphere. It is not designed to fetch delta data from remote tables.
* C. Replication Flow:A Replication Flow is specifically designed to replicate data from a source system to a target system. It supports both full and delta data replication, making it the correct choice for fetching delta data from a remote table in the SAP BW bridge space.
* D. Data Flow:A Data Flow is a general-purpose object used to define data extraction, transformation, and loading processes. While it can handle data movement, it does not inherently focus on delta data replication.
Key Concepts:Analysis of Each Option:Why Replication Flow is Correct:Replication Flow is the only Data Builder object explicitly designed to handle delta data replication. When configured for delta replication, it identifies and extracts only the changes (inserts, updates, or deletes) from the remote table in the SAP BW bridge space, ensuring efficient and up-to-date data synchronization.
References:SAP Datasphere Documentation: The official documentation highlights the role of Replication Flows in fetching delta data from remote systems.
SAP BW Bridge Documentation: The SAP BW bridge supports real-time data replication, and Replication Flows are the primary mechanism for achieving this in SAP Datasphere.
SAP Best Practices for Data Replication: These guidelines recommend using Replication Flows for incremental data loading to optimize performance and reduce resource usage.
By using a Replication Flow, you can efficiently fetch delta data from a remote table in the SAP BW bridge space.

NEW QUESTION # 27
What are the prerequisites for deleting business partner attribute master data in SAP BW/4HANA? Note:
There are 2 correctanswers to this question.

A. In SAP BW/4HANA there must be no analysis authorizations related to business partner values that should be deleted
B. There must be no BW query as InfoProvider in SAP BW/4HANA that uses business partner as a free characteristic.
C. There must be no transaction data in a DataStore Object (advanced) referring to business partner values that should be deleted.
D. In SAP BW/4HANA there must be no hierarchy data related to business partner values that should be deleted.

Answer: C,D

NEW QUESTION # 28
Which node type is available for both graphical modeling of SAP HANA HDI Calculation Views (XS Advanced) and SAP HANA Calculation Views (XS Classic)?

A. Rank
B. Minus
C. Non Equi Join
D. Graph

Answer: A

NEW QUESTION # 29
What are some of the variable types in a BW query that can use the processing type SAP HANA Exit? Note:
There are 2 correctanswers to this question.

A. Text
B. Characteristic value
C. Formula
D. Hierarchy node

Answer: B,C

NEW QUESTION # 30
An upper-level CompositeProvider compares current values with historic values based on a union operation.
The current values are provided by a DataStore object (advanced) that is updated daily. Historic values are provided by a lower-level CompositeProvider that combines different open ODS views from DataSources.
What can you do to improve the performance of the BW queries that use the upper-level CompositeProvider?
Note: There are 2 correct answers to this question.

A. Use the "Generate Dataflow" feature for the Open ODS views load the historic data to the new generated DataStore objects (advanced).
B. Use a join node instead of the Union node in the upper-level CompositeProvider.
C. Replace the DataStore object (advanced) for current data by an Open ODS view that accesses the current data directly from the source system.
D. Replace the lower-level CompositeProvider with a new DataStore object (advanced) fill it with the same combination of historic data.

Answer: A,D

Explanation:
Improving the performance of BW queries that use a CompositeProvider involves optimizing the underlying data sources and their integration. Let's analyze each option to determine why A and D are correct:
* Explanation: CompositeProviders are powerful tools for combining data from multiple sources, but they can introduce performance overhead due to the complexity of union operations. Replacing the lower- level CompositeProvider with a DataStore object (advanced) simplifies the data model and improves query performance. The DataStore object can be preloaded with the combined historic data, eliminating the need for real-time union operations during query execution.
* In SAP BW/4HANA, DataStore objects (advanced) are optimized for high-performance data storage and retrieval. They provide faster access compared to CompositeProviders, especially when dealing with static or semi-static data like historic values.
2. Use a join node instead of the Union node in the upper-level CompositeProvider (Option B) Explanation: Replacing a Union node with a Join node is not always feasible, as these operations serve different purposes. A Union combines data from multiple sources into a single dataset, while a Join merges data based on matching keys. If the data model requires a Union operation, replacing it with a Join would fundamentally alter the query logic and produce incorrect results.
Reference: The choice between Union and Join depends on the business requirements and data relationships.
Performance improvements should focus on optimizing the existing Union operation rather than replacing it with an incompatible operation.
3. Replace the DataStore object (advanced) for current data with an Open ODS view that accesses the current data directly from the source system (Option C)Explanation: Accessing current data directly from the source system via an Open ODS view can introduce latency and increase the load on the source system.
Additionally, this approach bypasses the benefits of staging data in a DataStore object (advanced), such as data cleansing and transformation. For optimal performance, it is better to retain the DataStore object for current data.
Reference: SAP BW/4HANA emphasizes the use of DataStore objects (advanced) for staging and processing data before it is consumed by queries. This ensures consistent performance and reduces dependency on external systems.
4. Use the "Generate Dataflow" feature for the Open ODS views and load the historic data to the newly generated DataStore objects (advanced) (Option D)Explanation: The "Generate Dataflow" feature automates the process of creating dataflows for Open ODS views. By loading historic data into newly generated DataStore objects (advanced), you consolidate the data into a single, optimized storage layer. This eliminates the need for complex unions and improves query performance.
Reference: SAP BW/4HANA provides tools like "Generate Dataflow" to streamline data modeling and integration. Using DataStore objects (advanced) for historic data ensures efficient storage and retrieval.
ConclusionThe correct answers areA (Replace the lower-level CompositeProvider with a new DataStore object (advanced) and fill it with the same combination of historic data)andD (Use the "Generate Dataflow" feature for the Open ODS views and load the historic data to the newly generated DataStore objects (advanced)). These approaches simplify the data model, reduce query complexity, and improve overall performance.

NEW QUESTION # 31
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