SAP C_PAII10_35 Exam Description:
This certification exam validates that the candidate possesses the fundamental and core knowledge required of the consultant profile. This certification proves that the candidate has an overall understanding and in‐depth technical skills to participate as a member of a project team in a mentored role. This certification exam is recommended as an entry level qualification to allow consultants to get acquainted with the fundamentals of SAP Predictive Analytics including how the various capabilities of SAP Predictive Analytics provide insights into specific business predictive analytics challenges.
Advanced examination information
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C_PAII10_35 Exam Certification Details:
| Cut Score: | 68% |
| Level: | Associate |
| Duration: | 180 mins |
| Languages: | English |
| Exam: | 80 questions |
| Sample Questions: | SAP C_PAII10_35 Exam Sample Question |
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SAP C_PAII10_35 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Time Series with Modeler | 8% - 12% | - Forecast analysis - Time series model creation |
| Topic 2: Data Manager | <8% | - Data manipulation and dataset creation - Scheduling and task management |
| Topic 3: Classification Modeling with Modeler | 12% | - Classification model building - Model evaluation and application |
| Topic 4: Introduction to Predictive Analytics | 12% | - Fundamental predictive analytics concepts - Key features of SAP Predictive Analytics |
| Topic 5: Predictive Factory | 12% | - Predictive Factory architecture and components - Model deployment and management |
| Topic 6: Social and Recommendation | <8% | - Recommendation model usage - Social data analysis concepts |
| Topic 7: Regression Modeling with Modeler | <8% | - Regression model development - Validation and application of regression models |
| Topic 8: Basics of Automated Analytics | <8% | - Automated analytics core capabilities - Operational workflows |
| Topic 9: Clustering with Automated Analytics | 8% - 12% | - Clustering techniques and application - Analyzing cluster results |
| Topic 10: Data Science Supporting Automated Analytics | 8% - 12% | - Role of data science in predictive analytics - Data pre-processing |
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