Exam Name: SAP Certified Application Associate - SAP Predictive Analytics
Certification Provider: SAP
Corresponding Certification: SAP Certified Application Associate
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Failing the C-PAII10-35 means paying the registration fee all over again, plus weeks of lost momentum. The SAP Certified Application Associate - SAP Predictive Analytics practice material from 2Pass4sure is built to help you succeed on the first attempt, with 80 questions that mirror the scope of the official syllabus.
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, Scenario-based |
| Exam Price: | 599 USD |
| Real Exam Qty: | 80 |
| Passing Score: | 68% |
| Available Languages: | English |
| Certificate Validity Period: | Valid for two most recent solution releases |
| Exam Duration: | 180 minutes |
| Recommended Training: | PAII10 - SAP Predictive Analytics 3.3 |
| Exam Registration: | SAP Training & Certification Shop SAP Certification Hub |
| Sample Questions: | DOWNLOAD DEMO |
| 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/ |
SAP C-PAII10-35 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Regression Modeling with Modeler | 8%-12% | - Building regression models - Model validation and use cases - Interpreting regression outputs |
| Clustering with Automated Analytics | 8%-12% | - Model debriefing and validation - Applying clustering results - Building clustering models |
| Data Science Supporting Automated Analytics | 8%-12% | - Data encoding and transformation - Data partition strategies - Model curves and interpretation |
| Time Series Modeling with Modeler | 8%-12% | - Building and adjusting time series models - Forecasting and result analysis - Time series concepts |
| Predictive Factory | >12% | - Creating and scheduling tasks - Deviation analysis and monitoring - Key features and architecture |
| Data Manager | <8% | - Data transformation and preparation - Data profiling and quality checks - Data import and connection |
| Social and Recommendation Modeling | <8% | - Social network analysis basics - Recommendation algorithms |
| Introduction to Predictive Analytics | >12% | - Basic predictive modeling concepts - Key capabilities of SAP Predictive Analytics - Use cases for predictive algorithms |
| Classification Modeling with Modeler | 8%-12% | - Building classification models - Model performance evaluation - Deployment and application |
| Basics of Automated Analytics | <8% | - Data storage and preparation - Data types and variable roles - Handling missing values and outliers |
SAP C-PAII10-35 Exam — Answers to Your Questions
The SAP Certified Application Associate - SAP Predictive Analytics (exam code C-PAII10-35) is the exam you pass to earn the SAP Certified Application Associate - SAP Predictive Analytics certification, a credential at the Associate level. If you are mapping out a certification path with SAP, this exam is a milestone worth planning around.
The C-PAII10-35 exam includes 80 questions, and you have 180 minutes to complete them. With that many questions on the clock, pacing is part of the challenge: divide your time into rough blocks as you go, and flag the items that stall you so you can circle back at the end instead of burning minutes on a single question. A week or two before your exam date, sit at least one full timed session in the 2Pass4sure test engine under the same time limit, so the pace feels familiar rather than frantic on the day.
You need 68% to pass the C-PAII10-35 exam, and the official registration fee is 599 USD. That fee is due again in full for every retake, which makes thorough preparation the cheaper investment by far. Before you book your seat, test yourself with the 2Pass4sure practice questions until you are scoring comfortably above the passing mark on a consistent basis — it is the simplest way to avoid paying for the same exam twice.
No formal prerequisites; basic knowledge of data analysis and SAP terminology recommended
Eligibility rules can be adjusted by SAP over time, so before you register, confirm the current requirements on the official exam page: view the official C-PAII10-35 exam information.
You can book the C-PAII10-35 exam through the official registration channels below:
How the exam is taken: Computer-based testing at authorized centers or online via SAP Certification Hub.
SAP lists the following official training options for candidates preparing for this exam:
Once you have worked through the training, measure your readiness with the 80 practice questions from 2Pass4sure — they show you exactly which topics still need attention before you book the exam.
Yes. 2Pass4sure offers a free PDF demo of the C-PAII10-35 practice questions, so you can judge the quality of the material firsthand before paying anything. Every purchase also includes 365 days of free updates — if SAP changes the exam during that year, your material changes with it. And when the free update period expires, you can extend it at a 50% discount from within your member zone.
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The official SAP Certified Application Associate - SAP Predictive Analytics outline divides the exam content into 10 main domains. The first three are:
- Time Series Modeling with Modeler — 8%-12%
- Social and Recommendation Modeling — <8%
- Predictive Factory — >12%
That is only the headline view — scroll back up to the Exam Topics section on this page for the complete domain-by-domain breakdown before you plan your study schedule.
SAP Certified Application Associate - SAP Predictive Analytics Sample Questions:
The term model carries many different meanings depending on its field of application. In data mining, a model describes and explains the relationships that exist between input data (one or more target variablest allows one to predict and explain phenomena, or to describe them. To quote George E.P. Box,
"All Models Are Wrong But Some Are Useful" from "Robustness is the Strategy of Scientific Model Building" in Robustness in Statistics. Eds., R.L. Launer and G.N. Wilkinson, 1979, Academic Press. A model that has satisfactory performance is one that possesses both:
Note: There are 2 correct answers to this question.
- A. Both of these ports must be accessible from the client machine. For example, network firewalls should allow communication on these ports between client machine and the servers.
- B. High explanatory power, that is, sufficient capacity to explain the target variable. This explanatory power is indicated by the predictive power of the model.
- C. High robustness, that is, sufficient capacity to repeat the same performance on new datasets containing observations of a similar nature to the training dataset. This explanatory power is indicated by the prediction confidence .
Correct Answer: B,C 🗳️
Once the model has been generated, you must verify its validity by examining the performance indicators:
Note: There are 4 correct answers to this question.
- A. The existing R is uninstalled and the registry entries and the R installation folder are removed from the machine.
- B. A quality indicator KI equal to 0.808,
- C. The prediction confidence defines the degree of robustness of the model, that is, its capacity to achieve the same explanatory power when applied to a new dataset. In other words, the degree of robustness corresponds to the predictive power of the model applied to an application dataset. For this scenario, the model generated has the following performance indicators:
- D. A robustness indicator KR equal to 0.992.
- E. The predictive power allows you to evaluate the explanatory power of the model, that is, its capacity to explain the target variable when applied to the training dataset. A perfect model would possess a predictive power equal to 1 and a completely random model would possess a predictive power equal to 0.
Correct Answer: B,C,D,E 🗳️
Once the modeling parameters are defined, you can generate the model. Then you must validate its performance using the predictive power Note: There are 2 correct answers to this question.
- A. Otherwise, you can modify the modeling parameters in such a way that they are better suited to your dataset and your business issue, and then generate new, more powerful models.
- B. The Detailed Log displays the details of each step of the process.
- C. If the model is sufficiently powerful, you can analyze the responses that it provides in relation to your business issue apply it to new datasets
- D. The Progress Bar displays the progression for each step of the process. It is the screen displayed by default.
Correct Answer: A,C 🗳️
The structure for a continuous variable is defined by
several intervals each made of :
Note: There are 4 correct answers to this question.
- A. a higher bound ([ ]) that can be either open or closed.
- B. With standalone installers on each targeted client system
- C. a minimum value (Minimum)
- D. a maximum value (Minimum)
- E. a lower bound ([ ]) that can be either open or closed,
Correct Answer: A,C,D,E 🗳️
To help you validate the description when using the Analyze option, you can display the first hundred lines of your dataset.
Note: There are 4 correct answers to this question.
- A. Click the button View Data. A new window opens displaying the dataset top lines.
- B. Set this group as the group owner of the tmp directory. This should be done if the application has been set up with a user account that has this group set as its primary group
- C. Click the Refresh button to see the selected rows.
- D. In the field Last Row Index, enter the number of the last row you want to display.
- E. In the field First Row Index, enter the number of the first row you want to display.
Correct Answer: A,C,D,E 🗳️
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