Creating a Model in SAP Analytics Cloud and Checking the Fact Table in SAP Datasphere

Objective

After completing this lesson, you will be able to create a model in SAP Analytics Cloud and check the fact table for the model in SAP Datasphere.

Integrated Data and Analytics

What is Seamless Planning?

Seamless planning is the integration of SAP Analytics Cloud and SAP Datasphere using SAP Analytics Cloud for planning and SAP Datasphere as a data platform creates a seamless planning solution.

Watch this short video introduction to find out how it works.

Requirements

All SAP Analytics Cloud for planning features are available for seamless planning models, including SAP Analytics Cloud predictive scenarios, however, there are some requirements. To use seamless planning:

  • SAP Analytics Cloud has to run on HANA Cloud.
  • SAP Analytics Cloud and SAP Datasphere tenants have to be linked for seamless planning in a 1:1 relationship by the system owner. Linking will enable the selection of SAP Datasphere spaces as the data storage location for the supported object types.
  • One SAP Analytics Cloud tenant can be linked with only one SAP Datasphere tenant.
  • You need to own licenses for both SAP Analytics Cloud and SAP Datasphere. In the seamless planning scenario, you would license the planning functionality via SAP Analytics Cloud users and license the hardware (storage, memory, compute) required for planning via SAP Datasphere capacity units.

Note

  • Only seamless planning models in Optimized Design Experience can be consumed.
  • The deployment of classic account models to SAP Datasphere is not supported.

More information and commonly asked questions can be found in the Technology Blogs by SAP post on seamless planning FAQ.

SAP Datasphere as a Data Storage Location

Create the Model

You still build your model in SAP Analytics Cloud even if you choose to store your data in SAP Datasphere. To create a model from a file that uses SAP Datasphere as the data storage location:

  1. In the Modeler in SAP Analytics Cloud, create a new model.
  2. In the Data Storage Location dialog, select SAP Datasphere. From the dropdown menu, select your SAP Datasphere space. Select Next. If you select SAP Analytics Cloud, then you cannot use seamless planning.
  3. In the Select a data source dialog, select File (Local File or File Server).
  4. In the Create Model from File dialog, use the Select Source File button, navigate to the file and select it. Once you select it, select Import.
The steps to creating a model that uses an SAP Datasphere space as the data storage location.

Expose the Model to SAP Datasphere

If you want to enable SAP Datasphere users to consume the model in SAP Datasphere, then model needs to be exposed. To do this:

  1. Enable Planning Capabilities by selecting the checkbox.
  2. Select Edit.
  3. In the SAP Datasphere Fact Table dialog, name the fact table. Select OK.
  4. Save the model.
The model created from a file with the Builder panel open. Steps 1-4 as identified above the screenshot are included.

SAP Analytics Cloud models expose the underlying data foundation as a Local Table (Fact), while the public dimension tables expose the master data as a Local Table (Dimension) associated with a translation table (storing the multi-language descriptions) and, in the future, hierarchy tables.

The model created from a file with the Builder panel open. Data Storage (SAP Datasphere section is highlighted with the model showing as Exposed.

Once a model is exposed, SAP Datasphere can use SAP Analytics Cloud-exposed objects in graphical views, SQL views, analytic models, transformation flows, for example. However, remember that SAP Analytics Cloud objects appear in read-only mode in SAP Datasphere, meaning that SAP Datasphere modelers cannot make structural changes to these objects.

Create a Model for Using SAP Datasphere as the Storage Location

Task 1: Create a Model for Plan Data Using the Data First Approach

Task Flow: In this practice exercise, you will:

  • Create a model in SAP Analytics Cloud from a file and connect it to an SAP Datasphere space
  • Configure the model Version and Date dimensions
  • Enable planning capabilities in the model
  • Expose the model to SAP Datasphere

Task 2: Create a Model for Actual Data Using the Data First Approach

This in an optional exercise. The process for creating a model with actual data and exposing it to SAP Datasphere is the same as creating the model for plan data, however, it is included to show how the model is set up as it is used in the other exercises in the lesson.

Task Flow: In this practice exercise, you will:

  • Create a model in SAP Analytics Cloud from a file and connect it to an SAP Datasphere space
  • Configure the model Version and Date dimensions
  • Enable planning capabilities in the model
  • Expose the model to SAP Datasphere

Fact Tables in SAP Datasphere

Access the SAP Datasphere Space

To access the fact table that was created when you exposed the model, open the SAP Datasphere space in the Data Builder.

SAP Datasphere Data Builder with the SACP21_41SEAMLESS_PLAN space highlighted.

View the Data

In the Data Builder of SAP Datasphere, you can see that the SAP Analytics Cloud model was successfully deployed and the SAP Analytics Cloud model was exposed with the semantic type Fact.

SAP Datasphere Data Builder with Fact_Table_Plan_Data highlighted.

When you open the fact table and select Data Viewer, you can view the model data. Since the model was exposed in read-only mode, you cannot change the structure from the Data Builder. Nevertheless, you can consume the model as the source in other workflows such as analytic models.

SAP Datasphere Data Builder fact table with Data Viewer selected. Model data is displayed in read-only mode.

Check the Fact Table in SAP Datasphere for the SAP Analytics Cloud Model

Task Flow: In this practice exercise, you will:

  • Access the Data Builder in SAP Datasphere
  • Check the fact table for the newly created SAP Analytics Cloud model