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SAP C_THR96_2311 Exam With Confidence Using Practice Dumps

Exam Code:
C_THR96_2311
Exam Name:
SAP Certified Application Associate - SAP SuccessFactors Workforce Analytics Technical Consultant 2H/2023
Vendor:
Questions:
80
Last Updated:
Jun 15, 2025
Exam Status:
Stable
SAP C_THR96_2311

C_THR96_2311: SAP Certified Application Associate Exam 2025 Study Guide Pdf and Test Engine

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SAP Certified Application Associate - SAP SuccessFactors Workforce Analytics Technical Consultant 2H/2023 Questions and Answers

Question 1

Which of the following SAP SuccessFactors Employee Central tables will be used most often as a Lookup table in SAP SuccessFactors Workforce Analytics on SAP HANA? Note: There are 2 correct answers to this question.

Options:

A.

Emp Employment Info table

B.

Fo Event Reason T table

C.

Emp Job Info T table

D.

Fo Pay Component T table

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Question 2

A customer wants to implement a Grade/Band dimension using the external code from the Fo Pay Grade T table. The source for all employee grade data is from the Pay Grade column in the Emp Job Info T table. Which table and columns do you use as Lookup Table, Lookup Column, and Source Column when configuring the Lookup?

Options:

A.

Fo Pay Grade T as Lookup Table. Code as Lookup Column. Emp Job Info T>Pay Grade as Source Column

B.

Emp Job Info T as Lookup Table. Pay Grade as Lookup Column. Fo Pay Grade T>Internal Code as Source Column

C.

Emp Job Info T as Lookup Table. Pay Grade as Lookup Column. Fo Pay Grade T>Code as Source Column

D.

Fo Pay Grade T as Lookup Table. Internal Code as Lookup Column. Emp Job Info T>Pay Grade as Source Column

Question 3

What can you use the Edit SQL button for when you add a dimension in the Dimensions screen? Note: There are 2 correct answers to this question.

Options:

A.

To source the hierarchy of dimension nodes from customer data

B.

To source the list of benchmarked dimension nodes from customer data

C.

To source the employees who are mapped to dimension nodes in customer data

D.

To source the labels for dimension nodes from customer data