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SAP Certified Associate - Data Engineer - Data Fabric Questions and Answers

Question 9

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

Options:

By using a BW query (update value set by query)

By accessing an SAP HANA HDI Calculation View of data category Dimension

By using a transformation data transfer process (DTP)

By entering the values manually

By referencing a table

Answer:

A, C, 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., ]

Question 10

Which options do you have to combine data from SAP BW bridge a customer space in SAP Datasphere core? Note: There are 2 correct answers to this question.

Options:

•Import SAP BW bridge objects to the SAP BW bridge space.

•Share the generated remote tables with the customer space.

•Create additional views in the customer space to combine data.

•Import SAP BW bridge objects to the customer space.

•Create additional views in the customer space to combine data.

•Import SAP BW bridge objects to the SAP BW bridge space.

•Create additional views in the customer space.

•Share the created views with the SAP BW bridge space to combine data.

•Import objects from the customer space to the SAP BW bridge space.

•Create additional views in the SAP BW bridge space to combine data.

Answer:

A, B

Explanation:

Combining data from SAP BW Bridge and the customer space in SAP Datasphere Core requires careful planning to ensure seamless integration and efficient data access. Let’s analyze each option to determine why A and B are correct:

Explanation:

Step 1: Importing SAP BW Bridge objects into the SAP BW Bridge space ensures that the data remains organized and aligned with its source.

Step 2: Sharing the generated remote tables with the customer space allows the customer space to access the data without duplicating it.

Step 3: Creating additional views in the customer space enables users to combine the shared data with other datasets in the customer space.

[: This approach leverages the concept of "remote tables" in SAP Datasphere, which provides a virtual link to the data in the SAP BW Bridge space. It avoids unnecessary data replication and ensures efficient data access., , 2. Option B: Import SAP BW bridge objects to the customer space and create views to combine dataExplanation:, Step 1: Importing SAP BW Bridge objects directly into the customer space simplifies the data model by consolidating all required data in one location., Step 2: Creating additional views in the customer space allows users to combine the imported data with other datasets within the same space., Reference: This approach is suitable when the customer space is the primary workspace for data modeling and analysis. It eliminates the need for cross-space sharing but may involve some data duplication., , 3. Option C: Import SAP BW bridge objects to the SAP BW bridge space, create views in the customer space, and share views with the SAP BW bridge spaceExplanation: Sharing views created in the customer space back to the SAP BW Bridge space is not a standard practice. Views in SAP Datasphere are typically used within the space where they are created, and sharing them across spaces can lead to complexity and inefficiency., Reference: SAP Datasphere emphasizes clear separation between spaces to maintain governance and performance. Cross-space sharing of views is not supported or recommended., , 4. Option D: Import objects from the customer space to the SAP BW bridge space and create views to combine dataExplanation: Importing objects from the customer space into the SAP BW Bridge space reverses the typical data flow and introduces unnecessary complexity. The SAP BWBridge space is designed to host data from SAP BW Bridge, while the customer space is intended for custom data modeling and integration., Reference: SAP Datasphere follows a unidirectional flow where data from SAP BW Bridge is shared with the customer space, not the other way around., ]

Question 11

A user has the analysis authorization for the Controlling Areas 1000 2000.

In the InfoProvider there are records for Controlling Areas 1000 2000 3000 4000. The user starts a data preview on the InfoProvider.

Which data will be displayed?

Options:

Data for Controlling Areas 1000 2000

No data for any of the Controlling Areas

Only the aggregated total of all Controlling Areas

Data for Controlling Areas 1000 2000 the aggregated total of 3000 4000

Answer:

Explanation:

Analysis Authorization in SAP BW/4HANA: Analysis authorizations are used to restrict data access for users based on specific criteria, such as organizational units (e.g., Controlling Areas). These authorizations ensure that users can only view data they are authorized to access.

InfoProvider: An InfoProvider is a data storage object in SAP BW/4HANA that holds data for reporting and analysis. When a user performs a data preview on an InfoProvider, the system applies the user's analysis authorizations to filter the data accordingly.

Data Preview Behavior: During a data preview, the system evaluates the user's analysis authorizations and displays only the data that matches the authorized values. Unauthorized data is excluded from the result set.

The user has analysis authorization forControlling Areas 1000 and 2000.

The InfoProvider contains records forControlling Areas 1000, 2000, 3000, and 4000.

When the user starts a data preview on the InfoProvider:

The system applies the user's analysis authorization.

Only data for the authorized Controlling Areas (1000 and 2000) will be displayed.

Data for unauthorized Controlling Areas (3000 and 4000) will be excluded from the result set.

B. No data for any of the Controlling Areas:This would only occur if the user had no valid analysis authorization or if there were no matching records in the InfoProvider. However, since the user is authorized for Controlling Areas 1000 and 2000, data for these areas will be displayed.Incorrect.

C. Only the aggregated total of all Controlling Areas:Aggregation across all Controlling Areas would violate the principle of analysis authorization, which restricts data access to authorized values. Unauthorized data (3000 and 4000) cannot contribute to the aggregated total.Incorrect.

D. Data for Controlling Areas 1000 2000 the aggregated total of 3000 4000:Unauthorized data (3000 and 4000) cannot be included in any form, even as part of an aggregated total. The system strictly excludes unauthorized data from the result set.Incorrect.

Key Concepts:Scenario Analysis:Why Other Options Are Incorrect:Why Option A Is Correct:The system applies the user's analysis authorization and filters the data accordingly. Since the user is authorized for Controlling Areas 1000 and 2000, only data for these areas will be displayed during the data preview.

SAP BW/4HANA Security Guide: The official guide explains how analysis authorizations work and their impact on data visibility in queries and data previews.

SAP Note on Analysis Authorizations: Notes such as 2508998 provide detailed guidance on configuring and troubleshooting analysis authorizations.

SAP Best Practices for Data Security: These guidelines emphasize the importance of restricting data access based on user roles and authorizations.

References:By leveraging analysis authorizations, organizations can ensure that users only access data they are authorized to view, maintaining compliance and data security.

Question 12

You created a generic DataSource in SAP ERP but did not release the DataSource for Operational Data Provisioning (ODP). What is the effect in SAP BW/4HANA?

Options:

The ODP DataSource can be generated using the DataFlow generation feature.

The ODP DataSource has to be created using the ODP_HANA source system type.

The ODP DataSource cannot be replicated using the ODP_SAP source system type.

The ODP DataSource has to be created using the ODP_SAP source system type.

Answer:

Explanation:

When working withOperational Data Provisioning (ODP)in SAP BW/4HANA, it is essential to release the DataSource in the source system (e.g., SAP ERP) for ODP before it can be used in the target system (SAP BW/4HANA). If the DataSource is not released for ODP, certain limitations arise during the replication process.

The ODP DataSource cannot be replicated using the ODP_SAP source system type (Option C):

In SAP BW/4HANA, when a DataSource is created in the source system (e.g., SAP ERP), it must be explicitly released for ODP to enable replication via theODP_SAP source system type.

If the DataSource is not released for ODP, the replication process will fail because the metadata required for ODP replication is not available in the source system.

This limitation applies specifically to theODP_SAP source system type, which relies on the ODP framework to extract data from SAP source systems.

The ODP DataSource can be generated using the DataFlow generation feature (Option A):While the DataFlow generation feature in SAP BW/4HANA simplifies the creation of data flows, it does not bypass the requirement to release the DataSource for ODP. Without releasing the DataSource, replication will still fail.

The ODP DataSource has to be created using the ODP_HANA source system type (Option B):TheODP_HANA source system typeis used for extracting data from SAP HANA-based sources, not SAP ERP or other SAP systems. This option is irrelevant to the scenario described.

The ODP DataSource has to be created using the ODP_SAP source system type (Option D):While the ODP_SAP source system type is used for SAP source systems, the issue here is not about creating the DataSource but rather about the inability to replicate it due to the lack of ODP release in the source system.

ODP Release Requirement:Releasing a DataSource for ODP in the source system ensures that the necessary metadata and extraction logic are available for replication in SAP BW/4HANA.

ODP_SAP Source System Type:This type is specifically designed for SAP source systems and relies on the ODP framework to manage delta queues and data extraction.

SAP Note 2358900 - Operational Data Provisioning (ODP) in SAP BW/4HANA:This note explains the requirements and steps for enabling ODP replication, including the need to release DataSources in the source system.

SAP BW/4HANA Data Modeling Guide:This guide provides detailed information on setting up and managing ODP connections between SAP BW/4HANA and source systems.

Link:SAP BW/4HANA Documentation

Correct Answer:Why Other Options Are Incorrect:Key Points About ODP and DataSource Replication:References to SAP Data Engineer - Data Fabric:By ensuring that the DataSource is released for ODP, you avoid replication issues and ensure seamless data extraction into SAP BW/4HANA.

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SAP Certified Associate - Data Engineer - Data Fabric Questions and Answers

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