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SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q71-Q76):

NEW QUESTION # 71
In which ODP context is the operational delta queue (ODQ) managed by the target system?

A. ODP_CDS
B. ODP_BW
C. ODP_HANA
D. ODP SAP

Answer: B

Explanation:
In the context ofOperational Data Provisioning (ODP), theoperational delta queue (ODQ)is a critical component that manages delta records for incremental data extraction. The management of the ODQ depends on the specific ODP context, particularly whether the target system or source system is responsible for maintaining the delta queue.
* ODP_BW (Option A):
* In theODP_BWcontext, theoperational delta queue (ODQ)is managed by thetarget system(SAP BW/4HANA).
* This means that SAP BW/4HANA takes responsibility for tracking and managing delta records, ensuring that only new or changed data is extracted during subsequent loads.
* This approach is commonly used when the source system does not natively support delta management or when the target system needs more control over the delta handling process.
* ODP_SAP (Option B):In theODP_SAPcontext, thesource system(e.g., SAP ERP) manages the operational delta queue. This is the default behavior for SAP source systems, where the source system maintains the delta queue and provides delta records to the target system upon request.
* ODP_CDS (Option C):TheODP_CDScontext is used for extracting data from Core Data Services (CDS) views in SAP HANA or SAP S/4HANA. In this context, delta handling is typically managed by the source system (SAP HANA or S/4HANA) and not the target system.
* ODP_HANA (Option D):TheODP_HANAcontext is used for extracting data from SAP HANA-based sources. Similar to ODP_CDS, delta handling in this context is managed by the source system (SAP HANA) rather than the target system.
* ODP_BW:
* Delta queue is managed by the target system (SAP BW/4HANA).
* Suitable for scenarios where the source system does not support delta management or when the target system requires more control.
* ODP_SAP:
* Delta queue is managed by the source system (e.g., SAP ERP).
* Default context for SAP source systems.
* ODP_CDS and ODP_HANA:
* Delta handling is managed by the source system (SAP HANA or S/4HANA).
* SAP Note 2358900 - Operational Data Provisioning (ODP) in SAP BW/4HANA:This note provides an overview of ODP contexts and their respective delta handling mechanisms.
* SAP BW/4HANA Data Modeling Guide:This guide explains the differences between ODP contexts and how they impact delta management in SAP BW/4HANA.
* Link:SAP BW/4HANA Documentation
Why Other Options Are Incorrect:Key Points About ODP Contexts:References to SAP Data Engineer - Data Fabric:By understanding the ODP context, you can determine how delta records are managed and ensure that your data extraction processes are optimized for performance and accuracy.

NEW QUESTION # 72
Which SAP solutions can leverage the Write Interface for DataStore objects (advanced) to push data into the inbound table of DataStore objects (advanced)? Note: There are 2 correct answers to this question.

A. SAP Datasphere
B. SAP Data Services
C. SAP Lscape Transformation Replication Server
D. SAP Process Integration

Answer: A,D

Explanation:
TheWrite Interface for DataStore objects (advanced)in SAP BW/4HANA enables external systems to push data directly into theinbound tableof a DataStore object (DSO). This interface is particularly useful for integrating data from various SAP solutions and third-party systems. Below is an explanation of the correct answers and why they are valid.
* A. SAP Process Integration
* SAP Process Integration (PI), now known asSAP Cloud Integration (CI), is a middleware solution that facilitates seamless integration between different systems. It can leverage the Write Interface to push data into the inbound table of a DataStore object (advanced).
* SAP PI/CI supports various protocols and formats (e.g., IDoc, SOAP, REST) to transfer data, making it a versatile tool for integrating SAP BW/4HANA with other systems.
* SAP PI/CI is widely used in enterprise landscapes to connect SAP BW/4HANA with external systems, including pushing data via the Write Interface.
D). SAP Datasphere
SAP Datasphere(formerly known as SAP Data Warehouse Cloud) is a cloud-based data management solution that integrates seamlessly with SAP BW/4HANA. It can use the Write Interface to push data into the inbound table of a DataStore object (advanced).
SAP Datasphere is designed for hybrid and cloud-first architectures, enabling organizations to consolidate and harmonize data across on-premise and cloud environments.
Reference: SAP Datasphere leverages the Write Interface to enable real-time or near-real-time data integration with SAP BW/4HANA, supporting modern data warehousing requirements.
Incorrect Options:B. SAP Lscape Transformation Replication Server
SAP Landscape Transformation Replication Server (SLT)is primarily used for real-time replication of data from SAP ERP systems to SAP HANA or other target systems. While SLT is a powerful tool for data replication, it does not directly use the Write Interface for DataStore objects (advanced).
Instead, SLT replicates data at the database level, bypassing the need for the Write Interface.
Reference: SLT operates independently of the Write Interface and is not listed as a supported solution for pushing data into DSOs.
C). SAP Data Services
SAP Data Servicesis an ETL (Extract, Transform, Load) tool used for data integration and transformation.
While it can load data into SAP BW/4HANA, it does not use the Write Interface for DataStore objects (advanced).
Instead, SAP Data Services typically loads data into staging areas or directly into target objects using standard ETL processes.
Reference: SAP Data Services is not designed to interact with the Write Interface, as it relies on its own mechanisms for data loading.
Conclusion:The correct answers areA. SAP Process IntegrationandD. SAP Datasphere, as these solutions are explicitly designed to leverage the Write Interface for DataStore objects (advanced) in SAP BW/4HANA.
They enable seamless integration and data transfer between external systems and SAP BW/4HANA.

NEW QUESTION # 73
You defined a condition in a BW query for the top 10 of 100 customers based on sales revenue.
Using key figure properties in the BW query which two scenarios regarding result presentation can be achieved? Note: There are 2 correct answers to this question.

A. One result row with the sales revenue sum of the top 10 customers a second result row with the sales revenue sum of the other 90 customers
B. One result row with the sales revenue sum of all 100 customers
C. One result row with the sales revenue sum of the top 10 customers
D. One result row with the sales revenue sum of the top 10 customers a second result row with the sales revenue sum of all 100 customers

Answer: A,C

Explanation:
In SAP BW queries, conditions and key figure properties are powerful tools for filtering and aggregating data to meet specific reporting requirements. When defining a condition in a BW query for the top 10 of 100 customers based on sales revenue, you can control how the results are presented by configuring the key figure properties. Below is an explanation of the correct answers:
C). One result row with the sales revenue sum of the top 10 customersThis scenario is achievable by applying aconditionin the BW query to filter for the top 10 customers based on sales revenue. The query will calculate the sum of sales revenue for only those top 10 customers and display it as a single result row. This approach focuses solely on the subset of data that meets the condition.
1: SAP BW/4HANA Query Designer allows users to define conditions (e.g., "Top N" filters) to restrict the dataset displayed in the query. The key figure properties can then be configured to aggregate the filtered data into a single result row.
D). One result row with the sales revenue sum of the top 10 customers a second result row with the sales revenue sum of the other 90 customersThis scenario is also achievable by combining aconditionwith the use ofexception aggregationorresult rowsin the BW query. Here's how it works:
The condition filters the top 10 customers based on sales revenue.
A second calculation is performed to aggregate the sales revenue for the remaining 90 customers (i.e., all customers not included in the top 10).
The query displays two result rows: one for the top 10 customers and another for the remaining 90 customers.
This approach requires careful configuration of key figure properties, such as exception aggregation (e.g., summing values outside the condition), to ensure accurate results.
Reference: SAP BW/4HANA supports advanced result calculations using exception aggregation and result rows. These features are documented in the SAP BW Query Design Guide and are commonly used to achieve detailed breakdowns of data.
Incorrect OptionsA. One result row with the sales revenue sum of all 100 customersThis scenario cannot be achieved directly when a condition is applied to filter for the top 10 customers. Applying a condition inherently restricts the dataset to only those customers that meet the condition (in this case, the top 10).
Therefore, the query will not include the sales revenue of all 100 customers unless the condition is removed.
Reference: Conditions in SAP BW queries are designed to filter data, and their application excludes non- matching records from the result set.
B). One result row with the sales revenue sum of the top 10 customers a second result row with the sales revenue sum of all 100 customersThis scenario is not achievable because the condition limits the dataset to only the top 10 customers. While you can calculate the sum of the top 10 customers, there is no mechanism within the same query to simultaneously calculate the sum of all 100 customers without removing the condition.
Reference: SAP BW queries do not allow overlapping calculations where a condition applies to one part of the dataset while ignoring the condition for another part of the same query.
ConclusionThe two correct scenarios regarding result presentation in this context are:
One result row with the sales revenue sum of the top 10 customers.
One result row with the sales revenue sum of the top 10 customers and a second result row with the sales revenue sum of the other 90 customers.
These scenarios leverage the capabilities of conditions, key figure properties, and exception aggregation in SAP BW queries to provide flexible and meaningful insights into the data.

NEW QUESTION # 74
What is the maximum number of reference characteristics that can be used for one key figure with a multi- dimensional exception aggregation in a BW query?

A. 0
B. 1
C. 2
D. 3

Answer: D

NEW QUESTION # 75
You created an Open ODS View on an SAP HANA database table to virtually consume the data in SAP BW
/4HANA. Real-time reporting requirements have now changed you are asked to persist the data in SAP BW
/4HANA.
Which objects are created when using the "Generate Data Flow" function in the Open ODS View editor?
Note: There are 3 correct answers to this question.

A. Data source
B. SAP HANA calculation view
C. CompositeProvider
D. DataStore object (advanced)
E. Transformation

Answer: A,D,E

Explanation:
* Open ODS View: An Open ODS View in SAP BW/4HANA allows virtual consumption of data from external sources (e.g., SAP HANA tables). It does not persist data but provides real-time access to the underlying source.
* Generate Data Flow Function: When using the "Generate Data Flow" function in the Open ODS View editor, SAP BW/4HANA creates objects to persist the data for reporting purposes. This involves transforming the virtual data into a persistent format within the BW system.
* Generated Objects:
* DataStore Object (Advanced): Used to persist the data extracted from the Open ODS View.
* Transformation: Defines how data is transformed and loaded into the DataStore Object (Advanced).
* Data Source: Represents the source of the data being persisted.
Key Concepts:Objects Created by "Generate Data Flow":When you use the "Generate Data Flow" function in the Open ODS View editor, the following objects are created:
* DataStore Object (Advanced): This is the primary object where the data is persisted. It serves as the storage layer for the data extracted from the Open ODS View.
* Transformation: A transformation is automatically generated to map the fields from the Open ODS View to the DataStore Object (Advanced). This ensures that the data is correctly structured and transformed during the loading process.
* Data Source: A data source is created to represent the Open ODS View as the source of the data. This allows the BW system to extract data from the virtual view and load it into the DataStore Object (Advanced).
* B. SAP HANA Calculation View: While Open ODS Views may be based on SAP HANA calculation views, the "Generate Data Flow" function does not create additional calculation views. It focuses on persisting data within the BW system.
* E. CompositeProvider: A CompositeProvider is used to combine data from multiple sources for reporting. It is not automatically created by the "Generate Data Flow" function.
References:SAP BW/4HANA Documentation on Open ODS Views: The official documentation explains the
"Generate Data Flow" function and its role in persisting data.
SAP Note on Open ODS Views: Notes such as 2608998 provide details on how Open ODS Views interact with persistent storage objects.
SAP BW/4HANA Best Practices for Data Modeling: These guidelines recommend using transformations and DataStore Objects (Advanced) for persisting data from virtual sources.
By using the "Generate Data Flow" function, you can seamlessly transition from virtual data consumption to persistent storage, ensuring compliance with real-time reporting requirements.

NEW QUESTION # 76
......

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