C_BW4H_2505 Exam Dumps - SAP Certified Associate - Data Engineer - SAP BW/4HANA

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Question # 4

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.

Reference characteristic

Transitive attribute

Compounding characteristic

Enhanced master data update

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Answer:

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., , , ]

Question # 5

What are the prerequisites for deleting business partner attribute master data in SAP BW/4HANA? Note: There are 2 correct answers to this question.

There must be no BW query as InfoProvider in SAP BW/4HANA that uses business partner as a free characteristic.

In SAP BW/4HANA there must be no hierarchy data related to business partner values that should be deleted.

There must be no transaction data in a DataStore Object (advanced) referring to business partner values that should be deleted.

In SAP BW/4HANA there must be no analysis authorizations related to business partner values that should be deleted

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Answer:

Explanation:

Deleting master data in SAP BW/4HANA requires careful consideration of dependencies to ensure data integrity and system stability. Below is a detailed explanation of the prerequisites for deleting business partner attribute master data:

Explanation: While it is important to ensure that queries do not rely on specific master data values, this is not a strict prerequisite for deleting master data. Queries using business partner as a free characteristic will not prevent the deletion of master data, as long as there are no active dependencies such as transaction data or authorizations tied to those values.

[: SAP BW/4HANA allows master data deletion even if queries reference the characteristic, provided there are no underlying dependencies like transaction data or authorizations., , Option B: In SAP BW/4HANA there must be no hierarchy data related to business partner values that should be deletedExplanation: While hierarchy data can be associated with master data, the presence of hierarchies does not directly prevent the deletion of master data. Hierarchies can be adjusted or removed independently of the master data deletion process. Therefore, this is not a prerequisite., Reference: SAP documentation does not list hierarchy data as a blocking factor for master data deletion unless the hierarchy itself has active dependencies., , Option C: There must be no transaction data in a DataStore Object (advanced) referring to business partner values that should be deletedExplanation: Transaction data in a DataStore Object (advanced) creates a dependency on the master data. If transaction data references specific business partner values, those values cannot be deleted until the transaction data is either archived or removed. This ensures data consistency and prevents orphaned records., Reference: SAP BW/4HANA enforces this rule to maintain referential integrity between master data and transactional data. Deleting master data without addressing transaction data would lead to inconsistencies., , Option D: In SAP BW/4HANA there must be no analysis authorizations related to business partner values that should be deletedExplanation: Analysis authorizations define access restrictions based on master data values. If analysis authorizations are configured to restrict access using specific business partner values, those values cannot be deleted until the authorizations are updated or removed. This ensures that security settings remain valid and consistent., Reference: SAP BW/4HANA checks for dependencies in analysis authorizations before allowing master data deletion. Failing to address these dependencies can result in authorization errors., , ]

Question # 6

Which entity can be used as a source of an Analytic Model?

Business entities of semantic type Dimension

Views of semantic type Fact

Tables of semantic type Hierarchy

Remote tables of semantic type Text

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Answer:

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.

Question # 7

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

Space

HDB module

Package

SQL script procedure

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Answer:

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 to support 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.

Question # 8

For InfoObject "ADDRESS" the High Cardinality flag has been set. However "ADDRESS" has an attribute "CITY" without the High Cardinality flag. What is the effect on SID values in this scenario?

SID values are not stored for InfoObject "ADDRESS".

SID values are generated when InfoObject "CITY" is activated.

SID values are generated when InfoObject "ADDRESS" is activated.

SID values are generated when data for InfoObject "ADDRESS" is loaded.

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Answer:

Explanation:

In SAP BW (Business Warehouse), the concept ofHigh Cardinalityplays a crucial role in determining how data is stored and managed for InfoObjects. Letâ€™s break down the scenario described in the question and analyze the effects on SID (Surrogate ID) values:

InfoObject: An InfoObject is a basic building block in SAP BW, representing a business entity like "ADDRESS" or "CITY".

High Cardinality Flag: When this flag is set for an InfoObject, it indicates that the InfoObject has a very large number of distinct values (high cardinality). This affects how SIDs are generated and managed.

SID (Surrogate ID): A unique identifier assigned to each distinct value of an InfoObject. SIDs are used to optimize query performance and reduce storage requirements.

InfoObject "ADDRESS": The High Cardinality flag is set for this InfoObject. This means that the system expects a large number of distinct values for "ADDRESS". As a result, SID generation for "ADDRESS" is deferred until actual data is loaded into the system. This approach avoids unnecessary overhead during activation and ensures efficient storage.

Attribute "CITY": This attribute does not have the High Cardinality flag set. Therefore, SIDs for "CITY" will be generated when the InfoObject is activated, as is typical for standard InfoObjects without high cardinality.

ForInfoObject "ADDRESS", since the High Cardinality flag is set,SID values are NOT generated during activation. Instead, they are generated dynamicallywhen data for "ADDRESS" is loadedinto the system. This behavior aligns with the design principle of high cardinality objects to defer SID generation until runtime.

Forattribute "CITY", SID values are generated during activation because it does not have the High Cardinality flag set.

Key Concepts:Scenario Analysis:Effects on SID Values:Why Option D is Correct:The correct answer isD. SID values are generated when data for InfoObject "ADDRESS" is loaded. This is consistent with the behavior of high cardinality InfoObjects in SAP BW. SID generation is deferred until data loading to optimize performance and storage.

[References:SAP BW Documentation on High Cardinality: SAP BW systems use the High Cardinality flag to manage large datasets efficiently. For high cardinality objects, SIDs are generated at runtime during data loading rather than during activation., SAP Note on SID Generation: SAP notes related to SID generation (e.g., Note 2008578) explain the behavior of high cardinality objects and their impact on SID management., SAP Data Fabric Best Practices: In scenarios involving high cardinality, deferring SID generation until data loading is recommended to ensure optimal performance and resource utilization., By understanding the implications of the High Cardinality flag and its interaction with attributes, we can confidently conclude that SID values for "ADDRESS" are generated only when data is loaded., ]

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