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SAP C_PAII10_35 Exam Questions

Status: RETIRED
Exam Name: SAP Certified Application Associate - SAP Predictive Analytics
Exam Code: C_PAII10_35
Related Certification(s):
  • SAP Certified Application Associate Certifications
  • SAP Predictive Analytics Certifications
Certification Provider: SAP
Number of C_PAII10_35 practice questions in our database: 80 (updated: 01-04-2022)
Expected C_PAII10_35 Exam Topics, as suggested by SAP :
  • Topic 1: Outline how to manipulate data in the Data Manager and how to use it to create dynamic data sets/ Introduction to Predictive Analytics
  • Topic 2: Using classification modeling, using regression modeling/ Build, debrief and apply a clustering model in Modeler
  • Topic 3: Build, debrief, save and apply a regression model in Modeler/ Data Science supporting Automated Analytics
  • Topic 4: Outline the key capabilities of SAP Predictive Analytics/ Clustering with Automated Analytics
  • Topic 5: Identify different data types, storage and variable roles/ Identify use cases for predictive algorithms
  • Topic 6: Build, debrief and apply a time-series model in Modeler/ Describe basic predictive modeling concepts
  • Topic 7: Creating and scheduling tasks, and using deviation analysis/ Classification Modeling with Modeler
  • Topic 8: Build and apply classification models in Modeler/ Describe the key features of SAP Predictive Factory
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Free SAP C_PAII10_35 Exam Actual Questions

Note: Premium Questions for C_PAII10_35 were last updated On 01-04-2022 (see below)

Question #1

Operation of Automated Analytic:

Note: There are 3 correct answers to this question.

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Correct Answer: A, B, C

Question #2

The different types of variables: continuous, ordinal and nominal are next encoded by the data encoding feature of Modeler, or by the Event Logging and Sequence Coding features in the case of dynamic dat

a. Before generating the model, you must:

Note: There are 2 correct answers to this question.

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Correct Answer: A, B

Question #3

You can then generate models, capable of either explaining and predicting a

phenomenon, or describing a dataset, in both cases, as a function of the previously

defined target variable. This phase is called the training phase. Once the models

have been generated, you can view and interpret their relevance and robustness

using:

Note: There are 2 correct answers to this question.

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Correct Answer: A, B

Question #4

Automated Analytics supports the following data sources:

Note: There are 2 correct answers to this question.

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Correct Answer: A, C

Question #5

The Periodic with testing at the end strategy distributes:

Note: There are 4 correct answers to this question.

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Correct Answer: A, B, C, D


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