SAP Analytic Cloud (SAC) Story on SAP Datasphere (DSP)
1. General
SAP Analytics Cloud (SAC) is a powerful frontend tool and offers multiple options to collaborate between users. Data for SAC Stories are coming from different data sources. Either from BW live connections, Native Models, S3 buckets and many more as well as SAP Datasphere. SAP DSP is for data storage, data governance, and data security. SAC is just a reporting tool with limited data management capabilities. SAP DSP is designed for long-term data storage and a centralized data management system, SAC aims to create an interactive dashboard and application used by end users.
This blog will show a Story based on SAP Datasphere (short: SAP DSP) and its current limitations. But first, this blog starts with preparing a data model for consumption within a SAC story.
2. Preparing a data model for Consumption in SAC
In contrast to a Business Warehouse integration, Datasphere has a different approach about modelling regarding metadata, variables and hierarchies.
Navigational attributes are modelled as own tables and are connected to the performance table as an association. The most common use case would be the time hierarchy.
- Time Hierarchy
- Product Hierarchy
- Location Dimension
2.1 Time Hierarchy
In order to use a time hierarchy, we can generate the table directly in your space, but it would be recommended to create this table within a space which shares this table with all spaces.
Go to your space and click on the Time Data Ribbon.
Select “Create Time Tables and Dimensions”
Setup the time range and namings.
2.2 Product Hierarchy
For the product hierarchy you can use your specific source table or derive the hierarchy information from the transactional data as in this example.
In order to do this, we will use a transformation flow to create a hierarchy specific to target table. In this case, I’ve used the SQL view in order to achieve this:
Transformation:
SELECT DISTINCT „Product ID“,“Product Name“,
„Category“
FROM „GPTOEXCEL“
Define the Target Table as Semantic Usage: Dimension and set the hierarchy accordingly.
2.3 Location Dimension
For the location dimension we followed the following blog which brings us to the overall Analytic Model layout:
3. Consume SAP DSP Model in SAC
By creating a live connection in the Connections area to your SAP Datasphere tenant, your content creators can build stories directly against the data that is modelled in SAP Datasphere. Live connections between SAC and SAP DSP can be established across tenants and data centres.
Any user with Execute permission on Other Data sources and Create, Read, Update, Delete, and Maintain permission on Connection can use this feature: create live data connections to SAP DSP systems, and access any SAP DSP Analytical Dataset, Analytic Model or Perspective within SAC.
Furthermore, to be able to consume SAP DSP data in stories, make sure that you have the DW Consumer role assigned in SAP DSP This role is required for SAP DSP data consumption in stories in SAC.
Results only display models and datasets that are exposed for consumption. Models, datasets or perspectives created before the Expose for Consumption option was introduced in SAP DSP, must be redeployed for them to appear in the search results.
Further information: https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/ad4281e2875949f0b4d45d1072ff4c38.html?locale=en-US
For example: On DSP side – Fact Views are generated from Data.
The view is then used to create an analytic model which is then possible to consume in SAC.
Afterwards and with the right authorization the user can select the model under the Datasphere Space:
Important note:
If the user wants to share a story based on a DSP Model, the receiving user needs to have access to the space where the model is based in.
Although it is possible to consume data from SAP DSP, there are limitations to the features supported by live SAP DSP connections to SAC. Planning and smart features for instance are not supported.
You would like to connect your existing SAC system with an SAP DSP system (in a different tenant and potentially in a different data center) and use SAP DSP as a live data source.
However, when working with an SAC live connection to SAP DSP, you experience certain product limitations in SAC (full list here):
In Analytics:
- Custom Shapes for Geo Maps are not supported
- Version based variance features are not supported on SAP DSP data.
- Version Mapping is not supported for SAP DSP data.
- Blending is not supported.
- Scheduling a Publication is not supported on SAP DSP data.
- Linked Dimension is only supported for SAP DSP models from the same Space. It is not supported across Spaces.
- R-Visualizations are not supported.
- Comment Widgets are not supported
- Copy Widgets between stories is not supported
- Import Pages from Stories that contain Datasphere models is not supported
In contrast, no issue when importing a page from a story which has another datasource based on a native model in SAC or BW live connection.
Stories in Classic Experience
- Blending is supported for the following scenarios:
- SAP DSP data with local SAC data
- SAP DSP data with SAP DSP data from the same Datasphere space.
- Blending information across Datasphere spaces, or across Datasphere tenants, or blending of Datasphere data with other Live Connections is not supported.
- Using Hyperlinks with the option „Apply selected dimension as filter“ enabled across Stories using SAP DSP Live Connections is not supported.
- SAP DSP Analytic models are not supported
4. Conclusion
As a current priority project at SAP, SAP DSP is in constant development as well as the connection to SAC to consume Data easier and create powerful stories.
Information on if and when those features may be supported you can find in the roadmap:
Also get a Training here: https://github.com/SAP-samples/teched2024-DA180