Designing Models

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Create a new model using public and private dimensions


Types of Model

A model represents a table of data. Example: Sales, Expense, and HR, etc.

SAP Analytics Cloud recognizes the following types of models:

Planning Model

Planning models are preconfigured with dimensions for time and version. They offer support for multi-currency and security features at the level of both model and dimension. When working with a planning model in a story, users with planning privileges can create their own versions of model data. These users can also write data to the model by typing new values, copying and pasting data, and using data actions.

Analytics Model

Unlike the planning model, the analytics model does not support categories, and does not require a time dimension. It is used for stories and analytic applications that are read-only, for data presentation and analysis purposes.

The figure above shows the comparison between datasets, planning models, and analytic models.


Both datasets and models can be used as data sources in stories.

A shareable live dataset can be created for SAP HANA. Live datasets can also be created from a story based on SAP Data Warehouse Cloud.

The New Model

The classic account model only allows one data/measure column in the transaction data table and therefore relied heavily on accounts to describe values for data such as revenue, cost, and administration.

The new model allows multiple data columns. For example, local currency amount, group currency amount, and quantity. Not all modeling features are supported in the new model, but will be added shortly. Eventually, only the new model will be available, but classic account models can be converted to New Models.

In the figure New Model Measures Price and Volume are the two data columns in the underlying transaction data table.

In the figure New Model Calculations the Price_x_Volume calculated measure is available to any story using this model. The calculated values are not stored in the underlying transaction data table.

In the figure New Model - Currency Conversion the converted measure is calculated on-the-fly and is not stored in the database.

Creating Models

Watch this video to learn about the data source options for creating a simple SAP Analytics Cloud model.

Viewing Options

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

  • Structure View

  • Data Foundation View

Select each highlighted option to navigate between the Structure view and the Data Foundation view.

Let's go into the details of each viewing option.

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 dimensions shows how many public versions there are, and whether there are any private versions. For date dimensions, the 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 do that 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.

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