SAP DataSphere Connector
This article explains to admins how to connect Gainsight to SAP DataSphere, create a data job, merge datasets, and transform and configure jobs or job chains in Gainsight.
Overview
SAP Datasphere is a cloud-based data service on the SAP Business Technology Platform (SAP BTP) that enables seamless data integration, cataloging, semantic modeling, and virtualization. It helps organizations unify, manage, and analyze their enterprise data effectively across diverse systems and environments.
Integrating Gainsight with SAP DataSphere allows you to ingest data into Gainsight standard objects (for instance Company and Person) and custom objects and provides deep insights into customer usage patterns.
Create a Connection
To connect SAP DataSphere with Gainsight, admins must obtain the SAP DataSphere credentials.
To create a connection:
- Navigate to Administration > Connectors 2.0.
- Click Create Connection. The Create Connection dialog appears.
- From the Connector dropdown, select SAP DataSphere.
- In the Name of the connection field, enter a name to identify the connection.
- Enter the credentials for the following fields:
- Database Host
- Schema Name
- Username
- Password
- Click Save
The SAP DataSphere is now connected to your Gainsight instance.
Context Menu Options
Admins can edit a connection with one of the following three vertical dots menu options, as required:
- Edit Connection: Update or modify the SAP DataSphere connection details.
- Delete Connection: Delete the SAP DataSphere connection.
Note: SAP DataSphere connection can be deleted when the associated job chains and data jobs are deleted first.
Create a Job
Admins can create jobs from the Administration > Connectors > Jobs page to sync data from required source objects with Gainsight. After selecting the Data Source, you can view all the SAP DataSphere objects in the left pane. Drag a source object to the Preparation screen to start creating a job.
For more information, refer to the Preparation of Connector Jobs article.
If the data jobs in a connection are dependent on each other, create a Job Chain and configure the schedule to the Job Chain. For more information, refer to the Configure Job or Job Chain Schedule article.
Merge Datasets
You can merge two or more datasets and create an output dataset. For example, you can merge datasets related to Bitcoin Cryptocurrency and Company datasets to know the list of transactions for each company and create an output dataset such as Company ARR.
For more information on Merge, refer to the Preparation of Connector Jobs article.
Transform Data
In the Preparation step of a connector job, you can transform data and add Case Fields to get more meaningful insights from the customer data.
The Transform function provides the capability to create or modify new case fields. The new case fields can be used to modify the external field as per the consumption requirement in Gainsight’s data model. Case fields can be defined to populate different values for different case conditions. For example, External picklist values such as New, Open, and Closed can be modified to Active and Inactive to match Gainsight’s picklist values.
For more information on how to use the Transform function, refer to the Preparation of Connector Jobs article.
Add Destination
Once the final output dataset is prepared, you can add a destination to the output dataset to sync data from the source to the target Gainsight object.
For more information on how to add a destination, refer to the Preparation of Connector Jobs article.
Direct Mappings
To sync data from an external system to Gainsight using Direct Mappings, you must map fields from the external system's source objects to Gainsight's target objects. The data sync happens based on the configured field mappings.
For more information on Direct Mapping, refer to the Preparation of Connector Jobs article.
Derived Mapping
(Optional) You can use Derived Mappings to populate values in an object's field (of the GSID data type) with values from the same or another standard Gainsight object. Lookup is used to accomplish this, and you can match up to six columns in the lookup.
Note: To use Derived Mappings, your Target Object must have at least one field of data type GSID.
For more information on Derived Mapping, refer to the Preparation of Connector Jobs article.
Job Chain
The Job Chain function helps simplify the process of scheduling a group of related jobs that you need to run in a particular sequence. This sequence is based on the scheduled time of the Job Chain.
For example, if Job A and B are to be executed in a sequence with Job B to automatically start as soon as Job A is completed, there is no need to schedule a job separately.
Note: When a job is added to a Job Chain, it follows the Job Chain's schedule, not its own, and executes in the sequence specified within the chain.
For more information on how to use Job Chains, refer to the Job Chain Page article.
Configure Job or Job Chain
After the job or job chain is configured, you can configure the Schedule for the job run. If there are multiple Jobs in a Connection that are dependent on each other, Gainsight offers an option to create a job chain to sync data in sequence.
For more information, refer to the Configure Job or Job Chain Schedule article.
Job Activities
You can view the Execution and Update Activities of all the data jobs on the Activity page. You can also download the error logs of the jobs from this page to help troubleshoot the configuration issues.
For more information, refer to the Activity Page article.