Buying for your company? Long-term relationships earn discounts — and old customers get priority on holiday sales coupons. The SAP Certified Application Associate - SAP Predictive Analytics test questions at Test4Cram: 80 practice questions for the C_PAII10_35 exam in 2026.
SAP C_PAII10_35 Exam Overview:
| Certification Vendor: | SAP |
|---|---|
| Exam Name: | SAP Certified Application Associate - SAP Predictive Analytics |
| Exam Number: | C_PAII10_35 |
| Exam Format: | Multiple choice |
| Passing Score: | 68% |
| Exam Price: | Varies by region (SAP Certification Hub exam pricing) |
| Exam Duration: | 180 minutes |
| Certificate Validity Period: | Valid for release; subject to SAP update/replacement |
| Real Exam Qty: | 80 |
| Available Languages: | English |
| Related Certifications: | SAP Certified Application Associate – SAP Analytics Cloud SAP Certified Application Associate – SAP Business Technology Platform SAP Certified Application Associate – SAP Data Intelligence |
| Sample Questions: |  |
| Exam Way: | Delivered through SAP Certification Hub (online proctored/exam center booking via SAP Training platform) |
| Pre Condition: | Familiarity with predictive analytics fundamentals and SAP Predictive Analytics components is recommended. |
| Official Syllabus URL: | https://training.sap.com/certification/C_PAII10_35 |
SAP C_PAII10_35 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Classification Modeling with Modeler | 12% | - Classification model building - Model evaluation and application |
| Topic 2: Introduction to Predictive Analytics | 12% | - Key features of SAP Predictive Analytics - Fundamental predictive analytics concepts |
| Topic 3: Social and Recommendation | <8% | - Social data analysis concepts - Recommendation model usage |
| Topic 4: Data Science Supporting Automated Analytics | 8% - 12% | - Role of data science in predictive analytics - Data pre-processing |
| Topic 5: Predictive Factory | 12% | - Predictive Factory architecture and components - Model deployment and management |
| Topic 6: Basics of Automated Analytics | <8% | - Automated analytics core capabilities - Operational workflows |
| Topic 7: Regression Modeling with Modeler | <8% | - Regression model development - Validation and application of regression models |
| Topic 8: Data Manager | <8% | - Scheduling and task management - Data manipulation and dataset creation |
| Topic 9: Time Series with Modeler | 8% - 12% | - Forecast analysis - Time series model creation |
| Topic 10: Clustering with Automated Analytics | 8% - 12% | - Analyzing cluster results - Clustering techniques and application |
SAP C_PAII10_35 Exam: Efficient Answers
Familiarity with predictive analytics fundamentals and SAP Predictive Analytics components is recommended. Eligibility rules change over time, so verify the current requirements on the official page (official C_PAII10_35 exam page) before registering.
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180 minutes for 80 questions. Practice in the Test4Cram soft or online version until testing feels casual — simulation removes the nerves.
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The SAP Certified Application Associate - SAP Predictive Analytics is SAP's certification exam for SAP Certified Application Associate, at the Associate level. When a good opportunity appears, the certified hold the vital advantages. Related credentials include SAP Certified Application Associate – SAP Analytics Cloud, SAP Certified Application Associate – SAP Business Technology Platform, SAP Certified Application Associate – SAP Data Intelligence.
Varies by region (SAP Certification Hub exam pricing) per attempt, 68% to pass. Fail and you pay twice or more — save time and money with the 80 practice questions for the C_PAII10_35 exam at Test4Cram.
The SAP Certified Application Associate - SAP Predictive Analytics blueprint spans 10 domains — including Time Series with Modeler (8% - 12%), Social and Recommendation (<8%), Basics of Automated Analytics (<8%). A cram sheet with direction beats aimless reading; the complete outline above lists every subtopic.
SAP Certified Application Associate - SAP Predictive Analytics Sample Questions:
If you let the structure as undefined, the application uses consistent
coder to automatically determine the categories grouping depending on their interaction with the target variable. You can configure two parameters in this case:
Note: There are 2 correct answers to this question.
- A. listing active connections, with information such as user, last activity time stamp, number of current models,
- B. listing the state of models being within each connection,
- C. Modeler - Data Encoding optimal grouping for all variables
- D. The band count for continuous variables
Correct Answer: C,D 🗳️
The operation of the Automated Analytics can be
subdivided into four phases:
Note: There are 4 correct answers to this question.
- A. Model presentation and deployment
- B. Data access
- C. Data manipulation and preparation
- D. Data modeling
- E. the Automated Analytics
Correct Answer: A,B,C,D 🗳️
A user has created several analyses with a chain in the
Predict room. What data can the user leverage in a
visualization in the Visualize room when these analyses
are executed successfully?
Note: There are 1 correct answers to this question.
- A. Data from all components from one analysis
- B. Data from one component from all analyses
- C. Data from one component from one analysis
- D. Data from all components from all analyses
Correct Answer: C 🗳️
To generate a time series model, you must select a partition strategy
to cut your training dataset into the three sub-sets: training, validation and testing. Since the order of the observations in the dataset is important for the modeling, only two types of partition strategies are available in time series:
Note: There are 2 correct answers to this question.
- A. In the IIS Administrative Tools pane, click Internet Information
Services (IIS) Manager. - B. Sequential with Testing
- C. Sequential without Testing
Correct Answer: B,C 🗳️
The Contributions by Variables plot allows you to examine the relative significance of each of the variables within the model. On this plot, each bar represents the contribution of an explanatory variable with respect to the target variable. The following four types of plots allow you to visualize contributions by variables:
Note: There are 4 correct answers to this question.
- A. Perform various analyses and build models on the data, including time series forecasting, outlier detection, trend analysis, classification analysis, segmentation analysis, and affinity analysis.
- B. Variable Contributions, that is, relative importance of each variable in the built model.
- C. Maximum Smart Variable Contributions, that is, the maximum smart variable contributions including only the maximum of similar variables. For example, only binned encoding of the continuous variable age will be displayed. This is the chart displayed by default.
- D. Smart Variable Contributions, that is, the variables internal contributions. Automated Analytics User Guides and Scenarios Modeler P U B L I C 97
- E. Variable Weights, that is, weights Guides and Scenarios Modeler P U B L I C 97
Correct Answer: B,C,D,E 🗳️
