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SAP C-BW4H-2404 Exam Syllabus Topics:

Topic
Details

Topic 1

Data Acquisition into SAP BW
4HANA: This section addresses the incorporation of diverse data origins into SAP BW
4HANA and the methodologies for data ingestion.

Topic 2

SAP Datasphere: This part investigates the implementation of SAP Datasphere, encompassing its modeling components and the SAP BW bridge capabilities.

Topic 3

Performance Optimization: This section scrutinizes elements associated with enhancing system efficiency.

Topic 4

SAP BW
4HANA Project and the Modeling Process: This segment offers direction on orchestrating SAP BW
4HANA initiatives.

Topic 5

Data Governance, Security, and Authorization: This part concentrates on safeguarding assets and information within SAP BW
4HANA and SAP HANA ecosystems.

Topic 6

Data Modeling and Design: This segment delves into the attributes and features of modeling entities within SAP BW
4HANA and SAP HANA HDI frameworks.

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SAP Certified Associate - Data Engineer - Data Fabric Sample Questions (Q13-Q18):

NEW QUESTION # 13
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. Business entities of semantic type Dimension
D. Remote tables of semantic type Text

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 # 14
Which development object needs to be built to generate an HDI Container?

A. HDB module
B. Package
C. Space
D. SQL script procedure

Answer: A

Explanation:
An HDB module is required to create and manage an HDI (HANA Deployment Infrastructure) container.
The HDB module includes the necessary configuration files and resources, such as.hdbcalculationviewor.
hdbtablefiles, which define objects to be deployed in the HDI container.
Reference: SAP HANA HDI documentation (SAP Help Portal - HDI).

NEW QUESTION # 15
Which development object needs to be built to generate an HDI Container?

A. HDB module
B. Package
C. Space
D. SQL script procedure

Answer: A

Explanation:
In the context of SAP HANA Deployment Infrastructure (HDI), anHDI Containeris a dedicated, isolated schema in the SAP HANA database that stores and manages database objects such as tables, views, procedures, and other artifacts. HDI Containers are used tosupport multi-target applications (MTAs) and enable developers to manage database objects in a structured and modular way.
* HDB Module (B):AnHDB moduleis a development object within the SAP Web IDE for SAP HANA or SAP Business Application Studio. It contains the database design-time artifacts (e.g.,.hdbtable,.
hdbview,.hdbsynonym) that define the structure and logic of the database objects. When you build an HDB module, it triggers the creation of an HDI Container if one does not already exist. The HDI Container is then populated with the runtime objects generated from the design-time artifacts defined in the HDB module.
* Key Points:
* The HDB module is part of a Multi-Target Application (MTA) project.
* It uses the HDI Deployer service to deploy the design-time artifacts into the HDI Container.
* The HDI Container ensures isolation and versioning of database objects, making it suitable for modern application development practices.
* Why Not the Other Options?
* Space (A):Aspaceis a concept in Cloud Foundry environments where applications and services are deployed. While spaces are used to organize and isolate resources, they are not directly related to generating an HDI Container. Spaces host applications and services but do not define the database objects required for an HDI Container.
* Package (C):In SAP HANA, apackageis a folder-like structure used to organize development objects in the SAP HANA repository. However, packages alone do not generate HDI Containers.
They are used in the classic repository-based development model (XSA or XS Classic), whereas HDI Containers are associated with the newer HDI-based development model.
* SQL Script Procedure (D):ASQL script procedureis a database artifact used to define procedural logic in SQL. While SQL script procedures can be deployed into an HDI Container, they are not responsible for generating the container itself. The container must already exist before deploying such artifacts.
Development Object Required to Generate an HDI Container:
SAP Data Engineer - Data Fabric Context:In theSAP Data Engineer - Data Fabriclandscape, HDI Containers play a crucial role in enabling modular and scalable data management. They allow developers to create isolated environments for different applications or tenants, ensuring data security and consistency. By leveraging HDB modules, developers can define and deploy database objects in a structured manner, aligning with modern DevOps practices.
For more information, refer to the following resources:
* SAP HANA Developer Guide for SAP HANA XS Advanced: Explains the role of HDB modules and HDI Containers in application development.
* SAP Business Application Studio Documentation: Provides guidance on creating and building HDB modules in the context of MTAs.
* SAP Learning Hub: Offers training on SAP HANA development, including HDI and MTA concepts.
By selectingB (HDB module), you ensure that the correct development object is identified for generating an HDI Container, enabling efficient database development and deployment.

NEW QUESTION # 16
You create a transformation from a DataSource to a DataMart Data Store object (advanced) All key figures are updated as Sum.
Which Delta methods indicate that the DataSource provides consistent information for this target? Note:
There are 2 correct answers to this question.

A. AIM
B. ADD
C. AIE
D. ABR

Answer: B,C

Explanation:
* B. ADD: This delta method indicates that the DataSource provides consistent information for this target.
It means that the DataSource delivers additive delta records with after images, which are updated directly in the delta queue. This can support sum aggregation for key figures12.
* D. AIE: This delta method indicates that the DataSource provides consistent information for this target.
It means that the DataSource delivers additive delta records with after images, which are updated in the extraction queue and then transferred to the delta queue. This can support sum aggregation for key figures13.
Reference:
* 1 https://wiki.scn.sap.com/wiki/display/BI/Delta+type+in+BW+Extractors
* 2 https://help.sap.com/doc/saphelp_nw73ehp1/7.31.19/en-
US/4f/18f6aa3fca410ae10000000a42189d/content.htm
* 3 https://help.sap.com/doc/saphelp_nw73ehp1/7.31.19/en-
US/4f/18f6b13fca410ae10000000a42189d/content.htm

NEW QUESTION # 17
You create an SAP HANA HDI Calculation View. What are some of the reasons to choose the data category Cube with Star Join instead of data category Dimension? Note: There are 3 correct answers to this question.

A. Combine master data and transactional data
B. Persist transactional data
C. Create restricted columns
D. Aggregate measures as a sum
E. Provide default time characteristics

Answer: A,B,D

NEW QUESTION # 18
......

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