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SAP C_BW4H_2505 Exam Syllabus Topics:

Topic
Details

Topic 1

• SAP BW
• 4HANA Modeling:This section targets the skills of Data Engineers in selecting appropriate modeling options and applying best practices like LSA++ within SAP BW
• 4HANA. It focuses on designing scalable, high-performing data models.

Topic 2

• SAP Analytics Tools and SAP Analytics Cloud: This section evaluates the skills of SAP Consultants in using tools like SAP Analytics Cloud, Lumira, and Analysis for Office to visualize and interpret data. It focuses on the consultant’s ability to apply business intelligence tools within the SAP ecosystem.

Topic 3

• InfoObjects and InfoProviders:This section tests the knowledge of Data Engineers in working with InfoObjects and InfoProviders in SAP BW
• 4HANA. It involves handling data structures used for organizing, storing, and accessing analytical data.

Topic 4

• SAP BW Query Design: This section of the exam assesses the ability of Data Engineers to create and run queries using SAP BW
• 4HANA. It evaluates how well candidates can work with query components to retrieve and structure data effectively for reporting and analysis.

Topic 5

• SAP BW
• 4HANA Project and the Modeling Process:This section of the exam assesses how Data Engineers guide and contribute to SAP BW
• 4HANA projects. It includes knowledge of modeling workflows, project lifecycle stages, and collaboration strategies within project teams.

 

SAP Certified Associate - Data Engineer - SAP BW/4HANA Sample Questions (Q53-Q58):

NEW QUESTION # 53
What are some of the advantages of using SAP BW/4HANA business content? Note: There are 2 correctanswers to this question.

• A. Automatic content activation during installation of SAP BW/4HANA
• B. Ability to modify business content objects to meet customer specific requirements
• C. Automatic generation of Analysis Authorizations during SAP BW/4HANA content activation
• D. Accelerated SAP BW/4HANA implementation using ready-made models

Answer: B,D

 

NEW QUESTION # 54
Which layer of the layered scalable architecture (LSA++) of SAP BW/4HANA is designed as the main storage for harmonized consistent data?

• A. Flexible Enterprise Data Warehouse Core layer
• B. Data Acquisition layer
• C. Open Operational Data Store layer
• D. Virtual Data Mart layer

Answer: A

Explanation:
TheLayered Scalable Architecture (LSA++)of SAP BW/4HANA is a modern data warehousing architecture designed to simplify and optimize the data modeling process. It provides a structured approach to organizing data layers, ensuring scalability, flexibility, and consistency in data management. Each layer in the LSA++ architecture serves a specific purpose, and understanding these layers is critical for designing an efficient SAP BW/4HANA system.
* LSA++ Overview:The LSA++ architecture replaces the traditional Layered Scalable Architecture (LSA) with a more streamlined and flexible design. It reduces complexity by eliminating unnecessary layers and focusing on core functionalities. The main layers in LSA++ include:
* Data Acquisition Layer: Handles raw data extraction and staging.
* Open Operational Data Store (ODS) Layer: Provides operational reporting and real-time analytics.
* Flexible Enterprise Data Warehouse (EDW) Core Layer: Acts as the central storage for harmonized and consistent data.
* Virtual Data Mart Layer: Enables virtual access to external data sources without physically storing the data.
* Flexible EDW Core Layer:TheFlexible EDW Core layeris the heart of the LSA++ architecture. It is designed to store harmonized, consistent, and reusable data that serves as the foundation for reporting, analytics, and downstream data marts. This layer ensures data quality, consistency, and alignment with business rules, making it the primary storage for enterprise-wide data.
* Other Layers:
* Data Acquisition Layer: Focuses on extracting and loading raw data from source systems into the staging area.It does not store harmonized or consistent data.
* Open ODS Layer: Provides operational reporting capabilities and supports real-time analytics.
However, it is not the main storage for harmonized data.
* Virtual Data Mart Layer: Enables virtual access to external data sources, such as SAP HANA views or third-party systems.It does not store data physically.
* Option A: Open Operational Data Store layerThis option is incorrect because the Open ODS layer is primarily used for operational reporting and real-time analytics. While it stores data, it is not the main storage for harmonized and consistent data.
* Option B: Data Acquisition layerThis option is incorrect because the Data Acquisition layer is responsible for extracting and staging raw data from source systems. It does not store harmonized or consistent data.
* Option C: Flexible Enterprise Data Warehouse Core layerThis option is correct because the Flexible EDW Core layer is specifically designed as the main storage for harmonized, consistent, and reusable data. It ensures data quality and alignment with business rules, making it the central repository for enterprise-wide analytics.
* Option D: Virtual Data Mart layerThis option is incorrect because the Virtual Data Mart layer provides virtual access to external data sources. It does not store data physically and is not the main storage for harmonized data.
* SAP BW/4HANA Modeling Guide: The official documentation highlights the role of the Flexible EDW Core layer as the central storage for harmonized and consistent data. It emphasizes the importance of this layer in ensuring data quality and reusability.
* SAP Note 2700850: This note explains the LSA++ architecture and its layers, providing detailed insights into the purpose and functionality of each layer.
* SAP Best Practices for BW/4HANA: SAP recommends using the Flexible EDW Core layer as the foundation for building enterprise-wide data models.It ensures scalability, flexibility, and consistency in data management.
Key Concepts:Verified Answer Explanation:SAP Documentation and References:Practical Implications:
When designing an SAP BW/4HANA system, it is essential to:
* Use the Flexible EDW Core layer as the central repository for harmonized and consistent data.
* Leverage the Open ODS layer for operational reporting and real-time analytics.
* Utilize the Virtual Data Mart layer for accessing external data sources without physical storage.
By adhering to these principles, you can ensure that your data architecture is aligned with best practices and optimized for performance and scalability.
References:
SAP BW/4HANA Modeling Guide
SAP Note 2700850: LSA++ Architecture and Layers
SAP Best Practices for BW/4HANA

 

NEW QUESTION # 55
Which entity can be used as a source of an Analytic Model?

• A. Views of semantic type Fact
• B. Tables of semantic type Hierarchy
• C. Remote tables of semantic type Text
• D. Business entities of semantic type Dimension

Answer: A

Explanation:
AnAnalytic Modelin SAP Data Fabric or SAP BW/4HANA is designed to analyze data by combining facts (measures) and dimensions (attributes). To create an Analytic Model, you need a source entity that represents the fact data. Below is a detailed explanation of why the correct answer is B:
* Incorrect: Business entities of semantic typeDimensionrepresent descriptive attributes (e.g., customer name, product category) rather than measurable data. While dimensions are essential for enriching fact data, they cannot serve as the primary source of an Analytic Model.
Option A: Business entities of semantic type Dimension
* Correct: Views of semantic typeFactcontain measurable data (e.g., sales revenue, quantity sold) and are the primary source for an Analytic Model. These views provide the numerical data required for analysis and reporting.
Option B: Views of semantic type Fact
* Incorrect: Tables of semantic typeHierarchydefine hierarchical relationships (e.g., organizational structures or product hierarchies). While hierarchies are useful for organizing and navigating data, they do not contain measurable data and cannot serve as the source of an Analytic Model.
Option C: Tables of semantic type Hierarchy
* Incorrect: Remote tables of semantic typeTextstore textual descriptions (e.g., product names, region names). These tables are used to enhance dimensions but do not contain measurable data and are not suitable as the source of an Analytic Model.
Option D: Remote tables of semantic type Text
* SAP Data Fabric Documentation: Explains the role of semantic types in defining the purpose of entities (e.g., Fact, Dimension, Hierarchy, Text).
* SAP BW/4HANA Modeling Guide: Describes how Analytic Models are built using fact data as the primary source and dimensions for contextual enrichment.
* SAP Analytics Cloud Integration: Highlights the importance of fact views in enabling advanced analytics and reporting.
References to SAP Data Engineer - Data Fabric ConceptsBy understanding the semantic types and their roles, you can effectively design Analytic Models that meet business requirements for data analysis and reporting.

 

NEW QUESTION # 56
You want to create a restricted column in an SAP HANA HDI calculation view.What do you need to define?
Note: There are 2 correctanswers to this question.

• A. A reference to an existing measure
• B. An aggregation method
• C. An SAP HANA data type
• D. A condition criterion

Answer: A,D

 

NEW QUESTION # 57
You define a remote subscription of type UPSERT in an SAP HANA Smart Data Integration (SDI) real-time update scenario.Which fields are added to the DataSource automatically?Note: There are 3 correctanswers to this question.

• A. SDI_LENTITY_COUNTER
• B. SDILCHANGE_TYPE
• C. SDILCHANGE_TIME
• D. SDILCHANGE_SEQUENCE
• E. SDILRECORD_MODE

Answer: B,C,D

 

NEW QUESTION # 58
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