Preparing Predictive Scenario Output Datasets

Objectives
After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Prepare predictive scenario output datasets to create an R visualization

Visualizing Output Data Generated by a Classification or Regression Predictive Scenario

There are three ways to create visualizations using output data generated from a classification or regression predictive scenario.

1. Consume the generated predictions in a story.

To create R visualizations using your output dataset in a story, you must ensure that the following is kept in the dataset:

  • The application data set variables, if these variables are not available from another source
  • The predictions
  • The key variable(s)

You can then upload the output data set directly in a story.

Once you check that the relevant information is in the dataset, you can create your story. This creates an embedded model in a story.

2. Combine existing data with the generated predictions and consuming them in a story.

It's also possible to add new data to a previously created prediction. To do this, you must keep the following information in your output dataset:

  • The predictions
  • The key variable(s)

Using the key variable, or variables, you can blend the predictions with other data sources in a story.

3. Import the output data set in SAP Analytics Cloud models.

You can create a model using the output dataset to create a story. From the story, you can create your R visualization.

Visualizing Output Data Generated by a Time Series Predictive Scenario

There are three ways to create visualizations using output data generated from a time series predictive scenario:

1. Consume your output data set in a story.

  • To consume your output data set in a story, you need the forecasts.
  • The date and signal are selected automatically.

Once you check that the relevant information is in the dataset, you can create your story. This creates an embedded model in a story.

2. Combine existing data with the generated predictions and consuming them in a story.

  • To combine existing data with your predictions, you need the forecasts in your output data set
  • The date and signal are selected automatically
  • Using the date variable, you can blend the predictions with other data sources, in the context of a story

3. Import the output data set in SAP Analytics Cloud models.

You can first use the output data set to create a model and then consume it in a story.

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