Pass your actual test with our SAP C_PAII10_35 training material at first attempt
Updated: Aug 11, 2026
No. of Questions: 80 Questions & Answers with Testing Engine
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| Certification Vendor: | SAP |
| Exam Name: | SAP Certified Application Associate - SAP Predictive Analytics |
| Exam Number: | C_PAII10_35 |
| Available Languages: | English |
| Real Exam Qty: | 80 |
| Certificate Validity Period: | Valid for two most recent solution releases |
| Exam Duration: | 180 minutes |
| Passing Score: | 68% |
| Exam Format: | Multiple Choice, Scenario-based |
| Exam Price: | 599 USD |
| Recommended Training: | PAII10 - SAP Predictive Analytics 3.3 |
| Exam Registration: | SAP Training & Certification Shop SAP Certification Hub |
| Sample Questions: | SAP C_PAII10_35 Sample Questions |
| Exam Way: | Computer-based testing at authorized centers or online via SAP Certification Hub |
| Pre Condition: | No formal prerequisites; basic knowledge of data analysis and SAP terminology recommended |
| Official Syllabus URL: | https://training.sap.com/certification/c_paii10_35-sap-certified-application-associate--sap-predictive-analytics-g/ |
The C_PAII10_35 exam is an important certification for professionals who work with data and need to be able to analyze it using predictive analytics techniques. It provides candidates with the necessary knowledge and skills to design, build, and deploy predictive models using SAP Predictive Analytics software. SAP Certified Application Associate - SAP Predictive Analytics certification is suitable for a wide range of professionals including data scientists, predictive modelers, business analysts, and others who work with data.
In order to be eligible for the SAP C_PAII10_35 certification exam, candidates must fulfill the eligibility criteria set by SAP. Candidates are required to have a basic understanding of predictive analytics, data modeling, and statistics. They should also possess some experience in using the SAP Predictive Analytics solution. Additionally, candidates must have a good command of the English language as the exam is conducted in English.
| Section | Weight | Objectives |
|---|---|---|
| Social and Recommendation Modeling | <8% | - Recommendation algorithms - Social network analysis basics |
| Clustering with Automated Analytics | 8%-12% | - Model debriefing and validation - Applying clustering results - Building clustering models |
| Predictive Factory | >12% | - Key features and architecture - Deviation analysis and monitoring - Creating and scheduling tasks |
| Classification Modeling with Modeler | 8%-12% | - Deployment and application - Building classification models - Model performance evaluation |
| Data Manager | <8% | - Data import and connection - Data transformation and preparation - Data profiling and quality checks |
| Introduction to Predictive Analytics | >12% | - Use cases for predictive algorithms - Basic predictive modeling concepts - Key capabilities of SAP Predictive Analytics |
| Regression Modeling with Modeler | 8%-12% | - Building regression models - Interpreting regression outputs - Model validation and use cases |
| Data Science Supporting Automated Analytics | 8%-12% | - Model curves and interpretation - Data partition strategies - Data encoding and transformation |
| Time Series Modeling with Modeler | 8%-12% | - Forecasting and result analysis - Time series concepts - Building and adjusting time series models |
| Basics of Automated Analytics | <8% | - Data types and variable roles - Data storage and preparation - Handling missing values and outliers |
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