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SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q78-Q83):

NEW QUESTION # 78
What foundation is necessary to use SAP S/4HANA embedded analytics?

A. SAP Agile Data Preparation
B. Generated external SAP HANA Calculation Views
C. ABAP CDS view based virtual data model
D. SAP HANA optimized business content

Answer: C

Explanation:
SAP S/4HANA Embedded Analytics relies on theABAP CDS (Core Data Services)view-based Virtual Data Model (VDM). This foundation provides a unified layer for data consumption directly from transactional data in the S/4HANA system.
* ABAP CDS Views as Foundation:
* CDS views define the semantic model for data and integrate seamlessly with SAP S/4HANA.
* These views allow users to build advanced reporting and analytics without requiring external data movement.
* Virtual Data Model (VDM):
* VDM provides a structured framework of CDS views optimized for analytics and reporting.
* It includes analytical, transactional, and consumption views tailored for SAP Analytics tools.
References:
SAP Help Portal - S/4HANA Embedded Analytics Overview
SAP Learning Hub - ABAP CDS View Basics

NEW QUESTION # 79
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 a second result row with the sales revenue sum of all 100 customers
D. One result row with the sales revenue sum of the top 10 customers

Answer: A,D

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 # 80
For which scenarios do you use the SAP HANA model focus? Note: There are 2 correct answers to this question.

A. Define ABAP Managed Database Procedures in data flows.
B. Load snapshots using ABAP CDS Views.
C. Build views procedures using SQL script.
D. Define calculations using geospatial functions.

Answer: C,D

Explanation:
TheSAP HANA model focusis a concept that emphasizes leveraging the native capabilities of SAP HANA for data modeling and processing. It is particularly useful when working with advanced features of SAP HANA, such as SQLScript, geospatial functions, and other in-memory database functionalities. The focus is on utilizing SAP HANA's high-performance computing capabilities to perform complex calculations and transformations directly within the database layer.
* SAP HANA Model Focus:The SAP HANA model focus is designed to maximize the use of SAP HANA's in-memory processing power. It involves creating models (e.g., calculation views, SQLScript procedures) that are optimized for performance and take full advantage of SAP HANA's advanced features.
* SQLScript:SQLScript is a scripting language in SAP HANA that allows developers to write procedural logic and perform complex calculations directly in the database. It is commonly used to build views and procedures that leverage SAP HANA's computational capabilities.
* Geospatial Functions:SAP HANA provides robust support for geospatial data and functions. These functions enable you to perform calculations and analyses involving geographical data, such as distances, areas, and spatial relationships.
* ABAP CDS Views and AMDPs:While ABAP CDS (Core Data Services) Views and ABAP Managed Database Procedures (AMDPs) are powerful tools for integrating SAP HANA with ABAP applications, they are not directly related to the SAP HANA model focus. These tools are more aligned with ABAP development and are typically used in scenarios where SAP HANA is integrated into an ABAP-based system.
* Option A: Load snapshots using ABAP CDS Views.This option is incorrect because loading snapshots using ABAP CDS Views is more aligned with ABAP development rather than the SAP HANA model focus. ABAP CDS Views are primarily used to define reusable data models in ABAP systems, and they do not fully leverage the native capabilities of SAP HANA.
* Option B: Build views procedures using SQL script.This option is correct because SQLScript is a core component of the SAP HANA model focus. Using SQLScript, you can create calculation views and procedures that are optimized for performance and take full advantage of SAP HANA's in-memory processing capabilities.
* Option C: Define ABAP Managed Database Procedures in data flows.This option is incorrect because ABAP Managed Database Procedures (AMDPs) are part of ABAP development and are used to execute database procedures from within ABAP programs. While AMDPs can interact with SAP HANA, they are not directly related to the SAP HANA model focus.
* Option D: Define calculations using geospatial functions.This option is correct because geospatial functions are a key feature of SAP HANA and align with the SAP HANA model focus. These functions allow you to perform advanced calculations involving geographical data, which is a common use case for leveraging SAP HANA's native capabilities.
* SAP HANA Developer Guide: The official documentation highlights the use of SQLScript and geospatial functions as key components of the SAP HANA model focus. It emphasizes the importance of leveraging these features to optimize performance and enable advanced analytics.
* SAP Note 2700850: This note provides guidance on using SQLScript and geospatial functions in SAP HANA and explains how these features can be integrated into data models.
* SAP HANA Academy: Tutorials and training materials from the SAP HANA Academy demonstrate how to use SQLScript and geospatial functions effectively in SAP HANA models.
Key Concepts:Verified Answer Explanation:SAP Documentation and References:Practical Implications:
When designing models in SAP HANA, it is important to:
* Use SQLScript to create calculation views and procedures that are optimized for performance.
* Leverage geospatial functions for scenarios involving geographical data, such as location-based analysis or mapping.
* Avoid relying on ABAP-specific tools (e.g., ABAP CDS Views or AMDPs) unless they are explicitly required for integration with ABAP systems.
By focusing on these aspects, you can ensure that your SAP HANA models are efficient, scalable, and aligned with best practices.
References:
SAP HANA Developer Guide
SAP Note 2700850: SQLScript and Geospatial Functions in SAP HANA
SAP HANA Academy: Advanced Modeling Techniques

NEW QUESTION # 81
What are the possible ways to fill a pre-calculated value set (bucket)? Note: There are 3 correct answers to this question.

A. By entering the values manually
B. By using a transformation data transfer process (DTP)
C. By accessing an SAP HANA HDI Calculation View of data category Dimension
D. By using a BW query (update value set by query)
E. By referencing a table

Answer: A,B,D

Explanation:
In SAP Data Engineer - Data Fabric, pre-calculated value sets (buckets) are used to store and manage predefined sets of values that can be utilized in various processes such as reporting, data transformations, and analytics. These value sets can be filled using multiple methods depending on the requirements and the underlying architecture. Below is an explanation of the correct answers:
A). By using a BW query (update value set by query)This method allows you to populate a pre-calculated value set by leveraging the capabilities of a BW query. A BW query can extract data from an InfoProvider or other sources and update the value set dynamically. This approach is particularly useful when you want to automate the population of the bucket based on real-time or near-real-time data. The BW query ensures that the value set is updated with the latest information without manual intervention.
* SAP BW/4HANA supports the use of queries to update value sets as part of its advanced data modeling and analytics capabilities. This functionality is well-documented in SAP's official guides on BW Query Design and Value Set Management.
C). By using a transformation data transfer process (DTP)The Transformation Data Transfer Process (DTP) is a powerful mechanism in SAP BW/4HANA for moving and transforming data between different objects. When filling a pre-calculated value set, a DTP can be configured to extract data from a source object (e.g., an InfoProvider or DataSource) and load it into the bucket. This method is highly efficient for large- scale data transfers and ensures that the value set is populated accurately and consistently.
Reference: SAP Data Engineer - Data Fabric leverages DTPs extensively for data integration and transformation tasks. The official SAP documentation on DTPs highlights their role in managing value sets and buckets.
D). By entering the values manuallyFor scenarios where the value set is small or requires specific customization, manual entry is a viable option. This method involves directly inputting the values into the bucket through the SAP GUI or other interfaces. While this approach is not scalable for large datasets, it provides flexibility for ad-hoc or one-time configurations.
Reference: SAP provides user-friendly interfaces for manually managing value sets, as documented in the SAP BW/4HANA Administration Guide. This feature is particularly useful during the initial setup or testing phases.
Incorrect OptionsB. By accessing an SAP HANA HDI Calculation View of data category DimensionWhile SAP HANA HDI Calculation Views are powerful tools for data modeling and analytics, they are not directly used to populate pre-calculated value sets in SAP BW/4HANA. Instead, these views are typically used for querying and analyzing data within the SAP HANA database. To fill a bucket, you would need to use a BW query or DTP rather than directly accessing an HDI Calculation View.
Reference: SAP HANA HDI Calculation Views are primarily designed for real-time analytics and are not integrated into the BW/4HANA bucket management process.
E). By referencing a tableReferencing a table is not a supported method for populating pre-calculated value sets in SAP BW/4HANA. Buckets are managed through specific mechanisms like queries, DTPs, or manual entry, and direct table references are not part of this workflow.
Reference: The SAP BW/4HANA documentation explicitly outlines the supported methods for bucket population, and table references are not included.
ConclusionThe three correct methods for filling a pre-calculated value set in SAP Data Engineer - Data Fabric are:
Using a BW query (update value set by query).
Using a transformation data transfer process (DTP).
Entering the values manually.
These methods align with SAP's best practices for managing value sets and ensure flexibility, scalability, and accuracy in data engineering workflows.

NEW QUESTION # 82
You notice that an SAP ERP ODP_SAP DataSource is delivering incorrect values into the first persistent data layer in SAP BW/4HANA. Which options do you have to analyze a potential extractor issue? Note: There are
2 correct answers to this question.

A. Use the transaction ODQMON (Monitor Delta Queues) in SAP BW/4HANA.
B. Check entries in the table RSDDSTATEXTRACT in SAP ERP.
C. Use the transaction RSA3 (Extractor checker) in SAP ERP.
D. Use the program RODPS_REPL_TEST in SAP ERP.

Answer: C,D

Explanation:
When dealing with incorrect values being delivered by an SAP ERP ODP_SAP DataSource into the first persistent data layer in SAP BW/4HANA, it is crucial to analyze potential issues at the extractor level in the SAP ERP system. Below is a detailed explanation of the correct answers:
* Explanation: The program RODPS_REPL_TEST is used to test the replication of data from an ODP_SAP DataSource in the SAP ERP system. It allows you to simulate the extraction process and verify whether the data being extracted matches the expected values. This helps identify issues with the extractor logic or configuration.
* RODPS_REPL_TEST is a standard tool provided by SAP for testing ODP-based DataSources. It is particularly useful for diagnosing issues related to data extraction in SAP ERP systems.
Option B: Use the transaction ODQMON (Monitor Delta Queues) in SAP BW/4HANAExplanation:
ODQMON is used in SAP BW/4HANA to monitor delta queues and ensure that data is being transferred correctly from the source system. However, it does not help analyze issues at the extractor level in the SAP ERP system. ODQMON focuses on the BW/4HANA side of the data transfer process.
Reference: ODQMON is primarily a monitoring tool for delta queues in BW/4HANA and is not suitable for diagnosing extractor issues in the ERP system.
Option C: Use the transaction RSA3 (Extractor checker) in SAP ERPExplanation: RSA3 is a powerful tool for testing and validating extractors in the SAP ERP system. It allows you to execute the extractor logic and view the extracted data directly in the ERP system. By comparing the extracted data with the expected values, you can identify issues such as incorrect mappings, filters, or transformations.
Reference: RSA3 is widely used for debugging extractor issues in SAP ERP systems. It is an essential tool for ensuring that DataSources deliver accurate data to SAP BW/4HANA.
Option D: Check entries in the table RSDDSTATEXTRACT in SAP ERPExplanation: The table RSDDSTATEXTRACT is not a valid or standard table in SAP ERP systems. It does not exist in the context of ODP_SAP DataSources or extractor diagnostics. Therefore, this option is incorrect.
Reference: SAP documentation does not mention RSDDSTATEXTRACT as a relevant table for analyzing extractor issues.
SummaryTo analyze potential extractor issues in the SAP ERP system:
RODPS_REPL_TEST: Simulates and tests the extraction process for ODP_SAP DataSources.
RSA3: Validates the extractor logic and verifies the extracted data.
These tools help identify and resolve issues at the extractor level, ensuring that correct data is delivered to the first persistent data layer in SAP BW/4HANA.

NEW QUESTION # 83
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