Creating an Import Model

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Create an import model

The Basics of Creating an Import Model

Creating an Import Model

Typically, you will begin creating your import model by choosing the + Model option and selecting the New Model. Then you will follow these basic steps:

  1. Add existing public dimensions.
  2. Create at least one measure. Currency related measures can either use a default currency or can be derived from a dimension with the currency property.

    When you add a measure to the model, the aggregation type will default to sum. The exception aggregation type can be used to manipulate aggregation. For example, a headcount measure could be set to an exception aggregation type of Last and an exception aggregation dimension of Date so that the model always reflects the headcount for a specific date, rather than the sum for all time.

    In the new model, you can also create calculated measures based on the existing measures in your model. Measure values are stored in the model; however, calculated and converted measures are refreshed when used and are not stored.

  3. Set the model preferences if needed, especially to define the model as Planning or not (Analytic). When you create a blank model, the default is the Planning model type, and Date and Version dimensions are included by the system. If you turn off the Planning preference to create an Analytic model, the Version dimension goes away, and the Date dimension becomes optional.
  4. Select the time range. When creating a new model, the default time range is from the current year to the current year plus one. For example, if the current year is 2024, the default time range will allow data for 2024 and 2025. But you can change the default range to meet your modeling requirements and match the data you will import into the model.
  5. Save the model. The model is ready for data imports.
A typical model has a Date dimension, Organization dimension, several Generic dimensions, and several Measures. It may also have an Account dimension, but in the new model, that dimension type is not required.

A Completed Analytic Model

Completed model:

  1. Model structure workspace: where you can view the meta data
  2. Measures: Where the measure values are stored in the model
  3. Public dimensions: Represented by a globe icon

Model Preferences

Preferences are set by default when the model is created and rarely changed except to specify an Analytic rather than a Planning model.

The following image shows the model preferences options.

Model Preferences

General Settings
Select the model type, either Planning or not (Analytic).
Request language translation.
Access and Privacy
Set data access and other controls.
Date Settings
Enable weekly based if needed and set the date to calendar year or fiscal year.
Set disaggregation behavior for planning models.
Enable currency conversion.
Structure Priority
Set the tie breaker for data intersections for account and measure formulas.
Data and Performance
Configure settings to optimize performance for analytics and planning.

Viewing Options

When creating a model, SAP Analytics Cloud has two viewing options:

  • Structure View
  • Data Foundation View

Access the Structure and Data Foundation views from the menu:

Structure View

The Structure view shows you a star schema diagram representing the contents of your model. This view helps you visualize how your fact data, attributes, and properties all relate to each other. At a glance, you can see the model's dimensions surrounding the data foundation.

Additionally the dimension box shows you more information based on the dimension type. For example, the Version dimension shows how many public versions there are, and whether there are any private versions. For Date dimensions, there is information about granularity and default hierarchy, and (if added) whether the Fiscal Year setting has been applied.

If you want to add a new dimension or existing dimension to your model, you can from the toolbar or from the Schema view.

Data Foundation View

The Data Foundation view shows you the fact table containing the raw, non-aggregated transactional data loaded into your model. The total number of results is the total number of rows of data, not including any filtering you have applied, across all versions.

In planning models, you can also switch between the different public versions of your data, for example, to see if data exists for a selected version.

The Structure and Data Foundation views work together with the Dimension List and Details panel to give you a consistent picture of your data. For example, if you select a dimension in the schema diagram, the other views all focus on that dimension.

Create an Import Model

Business Example

You need to create a new model to be used for weekly universe data. The weekly data should be organized in a time hierarchy with a 4-4-5 pattern. The data only needs to be analyzed, therefore, a planning model is not needed.

Task Flow

In this simulation, we will walk you through the steps in completing the following tasks:

  • Create an analytic new model
  • Enable a week-based data pattern
  • Allow data for a week granularity

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