api/v1/dataimport

Prerequisites

• You must have a SAP Analytics Cloud tenant URL.

• You must have a SAP Analytics Cloud user.

• You must have an SAP Analytics Cloud for planning, predictive standard edition or SAP Analytics Cloud for planning, predictive professional edition license.

• You must configure OAuth to work with your application. The Data Import Service supports three OAuth authentication flows:

  • OAuth 2.0 Client Credentials (2-legged OAuth) – This workflow allows administrators to access and import all data to any given models in machine-to-machine scenarios for example.

  • OAuth 2.0 SAML Bearer Assertion (2-legged OAuth) - This workflow allows administrators to access and export all data from any given models in machine-to-machine scenarios for example.

  • OAuth 2.0 Authorization Code Grant (3-legged OAuth) - This workflow allows business users to import smaller subsets of data while leveraging roles and data access privileges to ensure that they can only access data they have privileges for, at a model level.

  For more information, see Setting Up Authentication.

• You must set up your OAuth Client to work with the Data Import Service.

Licenses

The Data Import Service requires different licenses depending on the action you want to perform and endpoints you want to access.

Job Lifecycle and Retention Policy

An import job goes through several states during its lifecycle:

• READY_FOR_DATA: The job has been created successfully, and you can now post data to it via the post data endpoint.

• READY_FOR_VALIDATION: Data has been posted to the job. You can post more data to the job, validate it with the validation endpoint, or perform both validation and execution in one step by using the run endpoint.

• READY_FOR_WRITE: Data in the job has been validated. You can still post more data to the job or execute it with the run endpoint.

• PROCESSING: The job has been executed with the run endpoint, and the import is happening in the backend. Once completed the state will change to COMPLETED.

• COMPLETED: The import job has been completed, and any valid rows have been imported to the SAP Analytics Cloud model.

• FAILED: There was an error with the job and the import could not be completed.

The Data Import Service has a retention policy for old jobs. The service automatically deletes 15-day-old jobs, and any artifacts associated with the jobs.

Import Types

Units can also be assigned descriptions in each of the 39 supported languages. Creation, deletion and update of these units takes place through the T006A table. To provide the most compatibility with other SAP products, when importing data to the T006A table, only the standard SAP language column SPRAS needs to be specified. This is then used to fill the SAP Analytics Cloud specific language column automatically when executing the import. This is why you will not see the column LANGUAGE when exporting metadata through the Data Import Service, but you will see it when exporting metadata through the Data Export Service.

In the case of deleting data, the DeletedData section requires only the primary keys of the row to be deleted. In the case of the T006 (Unit Conversion Rates) table, this is the column MSEHI (Unit ID), and in the case of T006A (Unit Descriptions), these are the columns MSEHI (Unit ID) and SPRAS (SAP Language). Other columns can be included; however, they will have no effect on what row is deleted.

Mappings

You can map column names in the source data to column names in the target model during the import. When you post data to the job, the service automatically translates the column names according to the mapping you have specified.

You can either pass mappings when you create a job, in which case they are persisted and exist for the lifetime of the job, or when posting data, in which case they only take effect for that request. Mappings you send in the post data request also take precedence over mappings persisted for the job.

Mapping is sent as an object in the request body as shown below. The object lists property to value mappings which represent dimension names and column names. The dimension name on the SAP Analytics Cloud model is the property (on the left-hand side) and is mapped to the source column name as the value (on the right-hand side). This ordering allows you to map multiple dimensions in the target model to single columns in the source data. This means that specifying a single column in the data to be imported will fill the value into multiple dimensions on the target model.

Mapping: { 
	“targetDimension1”: “sourceColumnName”, 
	“targetDimension2”: “sourceColumnName2” 
} 

Default Values

Default values allow you to provide a value for a given column, which is then used for every row where a value for that column is not provided. If every row is to have the same value for a given column, or if you would like some rows to have a default value when none is provided, you can specify this in the default values section of your request when creating a job or when posting data to the job.

Default values provided when posting data to the job only apply during the current POST request and are not applied for subsequent POST requests, whereas default value provided during the job creation are applied to every POST of data. The most recent default value provided for a column is the one used.

DefaultValues: { 
    “targetDimension1”: “defaultValue1”, 
    “targetDimension2”: “defaultValue2” 
}