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SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q70-Q75):

NEW QUESTION # 70
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 a join node instead of the Union node in the upper-level CompositeProvider.
B. Replace the lower-level CompositeProvider with a new DataStore object (advanced) fill it with the same combination of historic data.
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. Use the "Generate Dataflow" feature for the Open ODS views load the historic data to the new generated DataStore objects (advanced).

Answer: B,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 # 71
You use a measure with semantic type "Amount with Currency Code" in your SAP HANA HDI calculation view.Which kind of currency reference can be assigned to the measure?Note: There are 2 correctanswers to this question.

A. Another column of the same SAP HANA view
B. A fixed currency from table TCURC
C. Acolumn from another SAP HANA view
D. A variable in the same SAP HANA view

Answer: A,D

NEW QUESTION # 72
What are the reasons for implementing Composite Providers? Note: There are 2 correct answers to this question.

A. To persist combined data for reporting
B. To directly expose an SAP HANA table from an external schema
C. To provide a virtual data mart layer that combines existing BW models
D. To provide an interface for using BW queries

Answer: A,C

Explanation:
Composite Providers in SAP BW/4HANA (part of the SAP Data Engineer - Data Fabric landscape) are essential components used to combine data from multiple sources into a unified view for reporting and analytics. They serve as a flexible tool for creating complex data models by integrating various BW objects, such as InfoProviders, Open ODS views, and external sources. Below is a detailed explanation of why Composite Providers are implemented:
* Explanation: Composite Providers can be configured to persist data by materializing the combined data into a physical table. This is particularly useful when you need to store intermediate results or optimize query performance for frequently accessed reports. Persisting data ensures faster access times and reduces the load on underlying systems.
* In SAP BW/4HANA, Composite Providers allow users to define whether the data should be persisted or remain virtual. This flexibility supports both real-time reporting and optimized batch processing scenarios.
Option B: To directly expose an SAP HANA table from an external schemaExplanation: This option is incorrect because Composite Providers are not designed to directly expose SAP HANA tables from external schemas. Instead, they focus on combining data from BW objects or other sources within the BW/4HANA environment. If you need to expose an external HANA table, you would typically use Open ODS views or other integration mechanisms.
Reference: SAP documentation emphasizes that Composite Providers are primarily used for combining BW models rather than exposing external HANA tables.
Option C: To provide an interface for using BW queriesExplanation: This option is incorrect because Composite Providers themselves do not directly provide an interface for BW queries. Instead, BW queries are built on top of InfoProviders, including Composite Providers. The role of a Composite Provider is to combine data, while BW queries are used to define the analytical logic and presentation layer.
Reference: According to SAP Data Engineer - Data Fabric guidelines, BW queries are created separately and consume the data exposed by Composite Providers or other InfoProviders.
Option D: To provide a virtual data mart layer that combines existing BW modelsExplanation: One of the primary purposes of Composite Providers is to create a virtual data mart layer. This allows users to combine existing BW models (e.g., InfoCubes, DataStore Objects, Open ODS views) without physically moving or duplicating data. By leveraging virtualization, Composite Providers enable real-time access to data while maintaining flexibility and reducing redundancy.
Reference: SAP BW/4HANA promotes the use of Composite Providers as part of its virtual data modeling capabilities, aligning with the principles of SAP Data Fabric to integrate and harmonize data across diverse sources.
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NEW QUESTION # 73
How does SAP position SAP Datasphere in supporting business users? Note: There are 3 correct answers to this question.

A. Business users can create agile models from different sources.
B. Business users can leverage embedded analytic Fiori apps for data analysis.
C. Business users can allocate system resources without IT involvement.
D. Business users can upload their own CSV files.
E. Business users can create restricted calculated columns based on existing models.

Answer: A,B,D

Explanation:
SAP Datasphere (formerly known as SAP Data Warehouse Cloud) is designed to empower business users by providing self-service capabilities while maintaining governance and scalability. Let's analyze each option to determine why A, B, and E are correct:
* Explanation: SAP Datasphere allows business users to create agile data models by integrating data from various sources, such as on-premise systems, cloud applications, and external datasets. This flexibility enables users to build models that reflect their specific business needs without heavy reliance on IT.
*The platform provides tools like the "Data Builder" and "Space Management" to facilitate the creation of models from diverse data sources. These tools are designed to be user-friendly, enabling business users to work independently.
2. Business users can leverage embedded analytic Fiori apps for data analysis (Option B)Explanation:
SAP Datasphere integrates with SAP Analytics Cloud (SAC) and other analytics tools, allowing business users to leverage embedded Fiori apps for data analysis. These apps provide pre-built dashboards and visualizations, enabling users to perform advanced analytics without requiring technical expertise.
Reference: Embedded analytics in SAP Datasphere supports real-time insights and decision-making, aligning with SAP's vision of empowering business users through intuitive tools.
3. Business users can allocate system resources without IT involvement (Option C)Explanation: While SAP Datasphere provides self-service capabilities, resource allocation (e.g., memory, CPU, storage) is typically managed at the administrative level to ensure optimal performance and governance. Business users do not have direct control over system resources to prevent misuse or over-allocation.
Reference: Resource management in SAP Datasphere is governed by administrators who define quotas and limits for spaces and users. This ensures that the system remains stable and scalable.
4. Business users can create restricted calculated columns based on existing models (Option D) Explanation: Creating restricted calculated columns requires a deeper understanding of data modeling and SQL scripting, which is typically beyond the scope of business users. This task is more suited for data engineers or power users who have technical expertise.
Reference: While SAP Datasphere supports advanced modeling features, these are often used by technical users rather than business users.
5. Business users can upload their own CSV files (Option E)Explanation: SAP Datasphere allows business users to upload CSV files directly into their spaces. This feature enables users to incorporate their own data into the platform for analysis and modeling, fostering agility and collaboration.
Reference: The ability to upload CSV files is part of SAP Datasphere's self-service capabilities, empowering business users to integrate personal or departmental data without IT intervention.

NEW QUESTION # 74
Which features of an SAP BW/4HANA InfoObject are intended to reduce physical data storage space? Note:
There are 2 correct answers to this question.

A. Reference characteristic
B. Transitive attribute
C. Enhanced master data update
D. Compounding characteristic

Answer: A,B

Explanation:
In SAP BW/4HANA, InfoObjects are fundamental building blocks used to define characteristics (attributes) and key figures in data models. They play a critical role in organizing and managing master data and transactional data. Certain features of InfoObjects are specifically designed to optimize storage and reduce physical data redundancy. Below is a detailed explanation of the correct answers:
* Explanation: A reference characteristic allows one characteristic to "reuse" the master data and attributes of another characteristic. Instead of duplicating the master data for the referencing characteristic, it simply points to the referenced characteristic's master data.This significantly reduces physical storage space by avoiding redundancy.
* In SAP BW/4HANA, reference characteristics are commonly used when multiple characteristics share the same set of values (e.g., "Country" as a reference for "Shipping Country" and "Billing Country"). This feature aligns with SAP Data Engineer - Data Fabric principles of optimizing data storage and minimizing duplication.
Option B: Transitive attributeExplanation: A transitive attribute is an attribute that is derived from another characteristic rather than being stored directly in the master data table of the main characteristic. For example, if "City" has an attribute "Region," and "Region" has an attribute "Country," then "Country" can be defined as a transitive attribute of "City." This avoids storing the "Country" attribute redundantly in the "City" master data table, thereby reducing physical storage requirements.
Reference: Transitive attributes are a key feature in SAP BW/4HANA for optimizing master data storage. By leveraging relationships between characteristics, they ensure that only necessary data is stored, adhering to the principles of efficient data management in SAP Data Engineer - Data Fabric.
Option C: Compounding characteristicExplanation: A compounding characteristic is used to create a hierarchical relationship between two characteristics, where one characteristic depends on another (e.g.,
"Street" compounded with "City"). While compounding helps organize data logically, it does not inherently reduce physical storage space.Instead, it defines how data is structured and queried.
Reference: Compounding is primarily a modeling feature and does not contribute to storage optimization.
Therefore, this option is incorrect.
Option D: Enhanced master data updateExplanation: The enhanced master data update mechanism improves the process of updating master data by enabling parallel processing and reducing update times.
However, it does not directly reduce physical storage space. Its purpose is to enhance performance and efficiency during data updates, not to optimize storage.
Reference: While enhanced master data update is a valuable feature in SAP BW/4HANA, it is unrelated to reducing physical storage space, making this option incorrect.
SummaryTo reduce physical data storage space in SAP BW/4HANA, the following features of InfoObjects are used:
Reference characteristic: Reuses master data from another characteristic, avoiding duplication.
Transitive attribute: Derives attributes indirectly through relationships, minimizing redundant storage.
These features align with the SAP Data Engineer - Data Fabric's focus on efficient data modeling and storage optimization.

NEW QUESTION # 75
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C-BW4H-2505 Actual Torrent - C-BW4H-2505 Pass-King Materials & C-BW4H-2505 Actual Exam

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SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q70-Q75):

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