Google Cloud and SAP: Successful integration of SuccessFactors and Analytics Cloud
- Google Cloud Platform, SAP Analytics Cloud
- 6 min reading time
Gary Lude
SAP Analytics Cloud (SAC) provides companies with a flexible and scalable platform for personnel cost planning (PCP). However, this planning requires seamless integration of master and transaction data from SAP SuccessFactors (SF). In order for SAC to apply the planning logic, it requires an extract of the data stock from SF.
Since there is no direct connector between SAC and SF, SAP Datasphere (DSP) and Google Cloud Services take on essential roles in data export and import. Different implementations can be selected, which are based on similar technical approaches. This results in high flexibility, adapted to your own requirements and existing infrastructure.
In the following section, the various expansion stages of the PKP with Google Cloud Services are described, and their specific characteristics and advantages are explained in detail.
Table of contents
Product 1: Optimized data provision and return via Google Cloud Services
The first solution uses the DSP as a central platform to provide data from SF for PKP in SAC. This solution is particularly suitable for companies that already rely on the DSP as a data integration platform.
Once the data has been transferred to the DSP, it is processed there so that the SAC can use it for the planning processes. After completion of planning in the SAC, the final planning data is stored within a data model. However, since the DSP is not able to import this planning data back to SF, Google Cloud plays a crucial role here.
The contents of the SAC Data Models are transferred to the Google Cloud via the SAC Export API. There, the data is transformed accordingly and then played back into the SF system via the SF API.
How does planning data import work?
As soon as the planning process in SAC is complete, the export of the planning data is triggered. A Google Cloud Scheduler is used to initiate the export process from SAC to Google BigQuery.
This process triggers a Google Cloud Function that uses the SAC Export API to transfer the data model to BigQuery. In BigQuery, the final plan data is then brought into the required format using a view. Additionally, this step applies the business logic to prepare the data for import into SF.
If the planning data is formatted correctly, another Cloud Scheduler can be activated. This starts a second Cloud Function, which imports the prepared data into the SF data stock via the SF API.
What are the advantages of this solution?
Features of the product
SF data extraction via DSP
Data is extracted from SF via the DSP because the modeling tools within SF and SAC are limited. The DSP serves as a central platform for exporting the required data. The relevant information is extracted from SF here and prepared for further processing. This step ensures that the master and transaction data are available in a structured format before being transferred to the SAC.
PKP within the SAC
Workforce planning is carried out in SAC after the data has been transferred from SF via DSP. Within SAC, planning logics and forecasts can be applied based on the SF data. SAC offers a flexible and customizable planning environment that can be tailored to the individual requirements of the company. Once planning is complete, the final plan data is stored in a data model within SAC to keep it available for further processing.
Importing SAC planning data via Google Cloud Services into SF
Once the personnel cost planning (PKP) is completed in SAC, Google Cloud Services takes over the data integration. The planned data is exported via the SAC Export API to Google BigQuery, where the data is transformed and prepared for import into SF. Finally, the planned data is transferred back into the SF system using the SF API. This process leverages the scalability and efficiency of the Google Cloud to ensure smooth and flexible data integration.
What opportunities are you missing without the product?
Without this solution, you miss the opportunity to efficiently and seamlessly implement the entire compensation planning process. Manual data reconciliation between SF and the SAC often leads to errors, delays, and increased effort. In addition, without the Google Cloud, you lack the ability to correctly transfer the planned data back into SF in the SAC after completion of the planning.
In addition, you miss out on the flexibility and scalability that Google Cloud offers. While manual or local systems quickly reach their limits, this solution allows you to efficiently process any amount of data, ensuring that your PKP works smoothly even with increasing demands. Lack of automation also means higher costs and longer decision times, which can lead to missed opportunities in agile business management.
Contact us for a consultation on integrating your SF data into the DSP and using it in the SAC with feedback via the Google Cloud.
Product 2: Efficient collaboration - How Google Cloud, SAP SuccessFactors and SAP Analytics Cloud connect
The second solution uses Google Cloud Services as a platform for data exchange with SAP SuccessFactors (SF) and SAP Analytics Cloud (SAC) without using SAP Datasphere (DSP). This approach is interesting for companies that do not use DSP and are looking for a cost-efficient infrastructure for personnel cost planning (PKP) in SAC.
Since the Google Cloud functions as a central platform, the required data is loaded directly from SF via the SF API into Google BigQuery. There, it is prepared for planning in SAC and brought into the required format. After planning, the finished plan data is exported from SAC via the SAC Export API back into BigQuery, where it is prepared again for re-import into SF. The last process step is analogous to product 1, regarding the return of plan data to SF via Google Cloud Services.
How does data exchange work?
To start the PKP, a Google Cloud Scheduler must be triggered, which starts a Cloud Function. This uses the SF API to export the planning data from the SF system to Google BigQuery. There, the individual tables are maintained and combined with views and business logic to form a final view for the SAC. These raw master and transaction data are then made available as a data model for the PKP via SAC Import Job (connection to BigQuery).
The return of the planning data from SAC to SF then takes place via the approach described in product 1.
What are the advantages of this solution?
Features of the product
SF data extraction via Google Cloud Services
The DSP was replaced by the Google Cloud as the central data platform, thus eliminating the need for a stand-alone PKP. The use of the SF API also simplifies the integration of so-called "custom fields," which are present in every modified SF system, as they are supplied by the API by default.
PKP within the SAC
Workforce planning is carried out in SAC after the data has been transferred from SF via DSP. Within SAC, planning logics and forecasts can be applied based on the SF data. SAC offers a flexible and customizable planning environment that can be tailored to the individual requirements of the company. Once planning is complete, the final plan data is stored in a data model within SAC to keep it available for further processing.
Importing SAC planning data via Google Cloud Services into SF
Once the personnel cost planning (PKP) is completed in SAC, Google Cloud Services takes over the data integration. The planned data is exported via the SAC Export API to Google BigQuery, where the data is transformed and prepared for import into SF. Finally, the planned data is transferred back into the SF system using the SF API. This process leverages the scalability and efficiency of the Google Cloud to ensure smooth and flexible data integration.
What opportunities are you missing without the product?
Without this solution, you will miss out on significant benefits in the area of compensation planning. The manual integration of data between SAP SF and the SAC is time-consuming and prone to errors.
Without Google Cloud Services, you lack automated and scalable data provisioning and feedback, which makes the entire planning process inefficient.
In addition, you benefit from the cost savings achieved by substituting the DSP, as Google Cloud optimally utilizes SF's native APIs and avoids costs for unused software components.
Contact us for a consultation on integrating your SF data with the Google Cloud and using it in the SAC.
