As of version 2021.03 it is possible to consume data from the DWC via live data connection in the SAC. In this blog article we will analyze this connection, looking at both the advantages and limitations.
What important factors need to be considered? SAC/DWC setting
In general there are two possibilities for consuming DWC data models and their data in the SAC:
- Space Aware Connectivity
Here the SAC is connected to the DWC automatically. Stories can be created based on DWC Spaces in the DWC context. For this integrated concept, the SAC and DWC must be located on the same tenant.
2. Cross Tenant Connectivity
With this connection it is possible to access analytical datasets from one or more DWC tenants in the SAC via live connection.
Two configuration steps are required for this:
DWC Configuration (Trusted Origin):
First, the URL of the SAC tenant in the DWC must be defined as trustworthy. This can be done in the embedded analytics administration of the DWC.
Under the App Integration tab, the original address of the SAC can be saved. Only after this is done can the connection be created in the SAC.
SAC Configuration (Connection Establishment and Story Creation)
Under Connections the creation of the Data Warehouse Cloud live connection can be configured. For this the DWC host name and the 443 HTTPS (TCP) port are required.
One of the special features of the DWC live connection is that it is no longer necessary to create a special SAC data model in the context of the SAC. In addition, in the SAC only analytical applications can be used as a data source from the DWC.
We created a use case on our test system in which we accessed the free ODATA Service (https://services.odata.org/V3/Northwind/Northwind.svc/). Here we noticed that the integration of DWC data models can be done very intuitively. There is no need for your own data model inside the SAC. All data model information, e.g. dimension and key figure allocations, can be used in the SAC context in the DWC – to define meta-information in a SAC model would be quite redundant.
To use the created DWC data model in the SAC, the data model must be configured for use. Here the “Analytic dataset” must be selected.
On the SAC tenant, you can then use this data right in the Story Builder.
Under Connect to Live Data, click on the DWC.
Select the DWC Space with which the data model is found.
And then search for the relevant model.
From the perspective of the hybrid SAC approach of connecting different data sources, the cross tenant connection is recommended. There, for example, there is no requirement of an identical tenant and thus there is no risk of having to undergo the painstaking process of creating stories from scratch in case of migration or a similar procedure.
Limitations of SAC Features through DWC Live Connection
Although at first glance most functionalities are available and a live reporting system can fulfill the most basic requirements, there are current DWC live connection limitations. We will take a closer look at these limitations in the following:
Calculation From (key figure)
This function is used to make a comparison of a key figure on different time periods. Here the key figure from the current date can be automatically compared with another date on a variable basis. In the current version this must be avoided.
CAGR – Compound annual growth Rate
CAGR is a function that is implemented in the SAC which automatically calculates and visualizes the growth rate of a key figure from a time perspective. As with other live connections this must be avoided.
Geomaps are useful when you have large amounts of data in aggregated form and can be allocated to regions or countries. If you use the live data connection to the DWC, then this is only possible if the data model contains information on longitude and latitude. If this is the case, however, the data can be displayed in bubble, heat and flow maps.
This function visualizes discrepancies with different versions (actual-plan comparison) or with specific time aggregations. But this helpful function has unfortunately not yet been implemented. Version mapping of, for example, actual and plan in the story is generally not yet available through DWC live data connection.
As is widely known, with the SAC it is possible to use many different sources for story building. For that reason it is rarely necessary for data from different sources to be combined together.
Currently, in the DWC live data connection blending is only possible in the following scenarios:
- DWC and local SAC data (file upload or replication)
- DWC data models that are located on the identical DWC space
The following are not possible:
- Data from a tenant but from multiple DWC spaces
- Data from different DWC tenants
- Data from other live-data connections, e.g. BW4H
Report distribution has an important role in many companies for sharing information with coworkers in a targeted fashion and at reliable time intervals. Currently the function is not supported in the SAC based on DWC data.
With the Data Analyzer, an ad-hoc analysis can be performed on the basis of a data model. For example, you can access a live data connection of a BW system directly in order to access queries in the SAC in a similar manner as in Analysis for Office. This functionality is not currently available on data in the DWC.
Many widgets can be assigned hyperlinks, which you can use to jump to a different story. Here all of the limitations of the sender chart can be brought over to the target story. This function is unfortunately not available in the DWC live connection.
As explained before, version mapping based on DWC data is not currently supported. SAC planning is likewise not currently available using DWC live connection as a basis.
DWC data types
The following data types from the DWC cannot be processed in the SAC:
- Large Binary
Limitation of smart features inside the SACE
Search to Insight
This is used to determine in natural language the selection result based on a model. Therefore, anyone with no SAC skills and using simple natural language can obtain a display of e.g. sales for a specific year or period. This feature is not available for the DWC live connection.
Analyzes the story, identifies noticeable characteristics in the diagram and shows more detailed information for the end user. As with other live connections, this function is not currently available.
Analyzes a data model through machine learning in order, for example, to identify key figure drivers and possible correlations. Here the data in the SAC itself must be available. This is a general limitation of live connections.
Here a data model can be trained with a training set in order to apply it to another data model. The user here has significantly more control over the security of forecasts, for example.
Is not currently supported on the basis of DWC data.
SAP Analysis for Microsoft Office
Currently neither the Analysis for Office add-in nor the AFO SAC edition can represent data that is created via DWC live connection.
To create the first simple stories, the current state of the functionalities in the SAC based on the DWC live connection is certainly a very good start. The integration of DWC data via live data connection is simple and most of all runs very fast, meaning that little time is expended for data model configurations in the SAC. Since it has been promised in the current SAP optimization roadmap, extended functionalities such as planning and report distribution should be possible in the near future. But these limitations should be taken into account beforehand before building the entire DWC reporting based on the SAC.