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Question No 1

SAP Predictive Analytics can be deployed in the following configurations: Note: There are 3 correct answers to this question.

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The desktop edition is a two - tier standalone configuration Both the Automated Analytics and Expert Analytics toolsets are available in the desktop edition.

The enterprise edition is a three - tier client - server configuration with server authentication.

If you have already installed SAP Predictive Analysis on your machine, you need to uninstall it before installing SAP Predictive Analytics.

The Automated Analytics toolset is available in the enterprise edition. With this configuration, you can install the following server - based components

Question No 2

If in the PAi Fiori application, a predictive model is shown in status error, more information about the cause may be found in the associated application log. If the PAi configuration is incorrect, which following messages may appear in the application log: Note: There are 2 correct answers to this question.

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Error: Invalid Table Message For example: invalid table name: sap.hana.pai.Engine::Entities.GTMP.PredictiveScenario: line 1 col 72 an indication that the PAi application is not installed correctly. The solution is to reinstall the PAi DU.

Error: ,QsuʨFLHQt Privilege For example: LnsuʨcLent privilege: Not authorized This means that the PAi HANA role The solution is to consult your database administrator regarding role assignment.

In Predictive Factory, you declare one or more modeling servers. (A modeling server is the machine that hosts the Automated Analytics server that will run the modeling tasks). Predictive Factory communicates with the Automated Analytics server using CORBA. All connections to data and model sources are handled via the modeling server.

Network administration is simplified because all network traffic from the client is directed to the server. This means only two TCP ports need to be opened for an Automated Analytics installation.

Question No 3

Once the PAi application is installed correctly, the most common expected error to be encountered is that the system does not have succulent rows of data to successfully build a predictive model. For the PAi application to work correctly, you need a minimum number of rows of data to train your predictive model. The number of required rows will vary from scenario to scenario and is dependent on the model type and the data. There are two main ways to handle this issue: Note: There are 2 correct answers to this question.

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If you have access to HANA logs, you will be able to see the full APL exception details and can investigate further.

The Predictive Factory server contains a group of services handled by the Server Intelligence Agent (SIA). The services can be stopped and started with the Start and Stop Predictive Factory commands.

You can verify the data via normal ABAP tools to see if succulent records are present. For example, by doing a data preview on the Predictive Scenario data source, taking into account any model version footer’s, you can see how many records are returned.

Communication between the Predictive Factory server and clients uses HTTP. You can configure encrypted communication (HTTPS) using Secure Sockets Layer (SSL) or Transport Layer Security (TLS)

Question No 4

Operation of Automated Analytic: Note: There are 3 correct answers to this question.

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Automated Analytics allows you to perform supervised data mining, that is, to transform your data into knowledge, then into action, as a function of a domain - specific business issue.

The application supports various formats of source data order to be usable by the application features, the dataset to be analyzed must be presented in the form of a single table of data, except in instances where you are using the Event Logging or Sequence Coding features of Data Manager.

To use the application’s features, you must have a training dataset available that contains the target variable with all its values defined. Then, you can apply the model generated using the training dataset to one or more application datasets.

The Predictive Factory server contains a group of services handled by the Server Intelligence Agent (SIA). The services can be stopped and started with the Start and Stop Predictive Factory commands

Question No 5

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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Describe the data. A utility integrated with the application allows you to generate a description of the dataset to be analyzed, automatically. You need only validate that description, verifying that the type and storage format of each variable were identified correctly.

Define the role of variables contained in the dataset to be analyzed. You may select one or more variables as target variables. These are the variables that corresponds with your business issue. The other variables of the table of data are considered to be explanatory variables: they allow calculation of the value of the target variable in a given context. They may also be used as weight variables.

Users are authenticated because clients must log in before being able to use the modeling server. User accounts can be configured to implement security policy.

Resources are used more fully because each modeling session has a dedicated process. The process size limit applies only to a single user

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