Import Data to Your Model

The process to import data differs depending on your model type, the data source, and the platform you are working on.

This section only describes how to import data to a model. After you import data, it must be prepared so that it's ready to be consumed both in models and stories. For more information about data preparation, check out Import and Prepare Fact Data for a Classic Account Model, or Import and Prepare Fact Data for a Model with Measures.

In the image below, you can see all the data sources supported when importing data to a model. Click any of them to access a detailed procedure.

This image is interactive. Hover over each area for a description. Click highlighted areas for more information.

Building a Query

Build a query to import data from an app or a data source into a new or existing model.

To build a query, you move data elements from the Available Data area into the Selected Data and Filters areas to create new measures and dimensions to be imported to your model, and apply filters to them.

An entity () can be expanded to select one or more of its members. The following icons represent types of data you can select, and their properties:

Icon Type
Numerical properties
Generic properties (strings, Boolean values, UUIDs, and so on)
Complex properties

In SAP Universe queries – the set of data that can be selected from and/or filtered on (similar to the Entity in other queries)

Date type properties
In SAP Universe queries – data that can be filtered on

When building a query, you can select the icon to search for specific values in the Available Data area, select the icon to display the list of reports from your source data in real time, or select the icon to change the way values are displayed:

  • Description – The Description is displayed and used to search values.
  • Description and ID – The Description and ID are both displayed. The ID is used to search values.
  • ID – The ID is displayed and used to search values.


When you add a data element to the Filters area, you can use operators, such as equal to, except, greater than, and so on, and select the icon to open the Select Values From dialog. In this dialog, you can search and select the values you want to filter on. The list displays the unique values from the first 1000 records. It is possible to search for a value not displayed in the list using the search function.

Some entities, such as Boolean values, can have only a single filter value. Entities such as strings or integer values can have multiple values in a filter. To select multiple values, select the check box of each value you want to add to the filter or Select All to select all the values in the list. Selecting multiple values for a single filter treats the filter as a large OR function, filtering out values that do not match any of the selected values.

Incremental Load Filters

When you create a query, you can set an Incremental Load. An incremental load is based on time or numeric data fields and lets you bring the newest set of data since the last import when you refresh. For example, you can set an incremental load based on the "Release Date" field of a "Product" entity to bring in the newest data based on the release date.

You can set an incremental load while creating a new data source or on an existing data source.
When you set an Incremental Load for the first time on a data source, the first refresh will not use the Incremental Load because the system doesn't know what the "newest" data is yet.

To set an incremental load, in the Filters area, select Set Incremental Load and then drag and drop an incremental-load-enabled property to the incremental load box that appears.


To ensure that duplicate data is not added during refresh, there are a few restrictions on the data field that you can use for an Incremental Load:

  • The values must be unique.
  • The data must be incremental.
  • Previously imported data must be unchanged.

Updates for previously imported data must be brought in by a new import using a specific query for that data region.

These restrictions are not enforced by the application, so you must ensure your data follows the restrictions.
After you create the model, the incremental load appears in the Import Settings section of the Data Management screen.

The incremental load will only take effect if there is a valid value recorded for the filter in the query builder or the import settings panel. Once an effective incremental load filter is present for your query, it is recommended to use Append as the import method for the data refresh job running that query. You can change the import method from the Import Settings section on the Data Management screen.

If you want to use the import method Update or Clean and replace subset of data, don't remove the Incremental Load field during wrangling. Otherwise, rows with the same dimensionality will be aggregated.

In addition, if you use Clean and replace subset of data pay special attention to the granularity of the date dimension used in your model. For more information on import methods, please see Update and Schedule Models.

The next time the source is refreshed, the latest value will be recorded for the Incremental Load Filter. Once the Incremental Load Filter has a value, you should switch the import method to Append.

Deleting or Replacing an Existing Incremental Load Filter

If you change the Incremental Load Filter to a different field, the new filter will not take effect until after the next refresh.


You set an Incremental Load based on the CreateDate field, and the latest row contains the date "Jan 14, 2018", so the system saves that value. The next time a data refresh occurs, a filter will be applied to grab only data that is later than "Jan 14, 2018".

If you change the Incremental Load to a different field, for example TransactionID, the system does not overwrite the old value until the next refresh. If you change the Incremental Load Filter back to CreateDate before a refresh, the load will still have the old value and, if you refresh now, it will still grab anything after "Jan 14, 2018".

To ensure the data is correct when you change an Incremental Load filter, make sure you perform the following steps:

  1. Change the Incremental Load Filter to a new field you want.
  2. Change the import method accordingly because the Incremental Load Filter will not apply right after you’ve switched it.
  3. Perform a manual refresh - The first refresh right after replacing or deleting the old incremental load filter will bring in the full set of data. Confirm a valid value is present for the incremental load filter after the manual refresh.
    Example of an Incremental Load Filter with a valid value
  4. Change the import method. More information.
  • These steps needs to be performed manually without the interruption of an automatic scheduled refresh job running on the same query.
  • If the data source was using the Append import method before using the Incremental Load Filter, then you can skip steps two to four.

Import Data into Public Dimensions

You can import master data from an external data source into a public dimension.


If you update model data by importing data into a model using the “Update dimension with new values” option, public dimensions are not updated. Follow this procedure to import data into public dimensions. Dimensions and their attributes can be imported:

  • Descriptions
  • Properties
  • Parent-child hierarchies

You can use this procedure to import data into public account dimensions as well. The following account dimension properties are supported at this time:

  • ID
  • Description
  • Account Type
  • Hierarchy
  • Unit Type
  • Measure Unit
  • Scale
  • Decimal Places
  • Rate Type

Unit Type and Measure Unit both correspond to the Units & Currencies column in the Modeler, for account dimensions.

The Unit Type value should be either Currency or Unit. When the value is Currency, the Measure Unit column is blank. When the value is Unit, the Measure Unit value can be a unit of measure or a packaging unit, such as Bottles or Pieces.

Importing Data Access Control Information

You can import data access control (DAC) information into a public dimension, to respect the access control that you've already defined in your on-premise system.

The DAC properties that can be imported are:

  • Read
  • Write
  • Data Locking Owner
  • Person Responsible

The values in the DAC column need to be formatted as follows:

  • Names separated by semicolons
  • All upper-case text

When you finish the column mapping and click Finish Mapping, a job will be submitted and shown in the Data Management tab. This job will start to run automatically after a few seconds, so you don't need to (and shouldn't) execute the job directly. Also, while the job is running, you can navigate away from the Data Management page; the job will continue to run in the background. When the job completes, a completion status will be displayed.

  • This feature is available for generic and organization dimensions, but not account dimensions.
  • Be sure that the user and team names to be imported are valid, because the information isn't validated during the import process.
  • Both user and team names are supported, but team names need to be prefixed with the keyword “TEAM:”. For example: TEAM:ABCTEAM.

The following procedure describes how to import data from a file into a public dimension. If you import data from other supported data sources, refer to the following topic for data-source-specific details:

Import Data to Your Model


  1. From the Modeler start page, go to the Public Dimensions tab.
  2. Select the check box beside the public dimension that you want to import data to.
  3. Select (Import Data).
  4. Choose the data source that you want to import data from; for example, File.
  5. In the Import Data From File dialog, choose whether you want to import data from a file on your local system, or from a file server.
    If you don't see the option to import data from a file server, see Allow Data Import and Model Export with a File Server.
  6. If you're importing from a file server, choose a file server connection, or select Create New Connection.

    If you create a new file server connection, specify the path to the folder where the data files are located. For example: C:\folder1\folder2 or \\servername\volume\path or /mnt/abc.

  7. Choose the file you want to import.
  8. If you are importing from a local Excel workbook containing multiple sheets, select the Sheet you want to import.
    If you are importing from an Excel file on a file server, the first sheet is automatically imported.
  9. Specify whether you want to use the first row of the data as column headers.
  10. If you're importing a .csv file, select which delimiter is used in the file.
  11. If the dimension specified in the Target Dimension field isn't correct, choose the correct one from the list.
  12. Select Import to begin the initial import of the source data.

    After the import completes, the data integration view is displayed, where you can complete the mapping of your new data to the public dimension.

    If you import a large-volume dataset, you'll be informed that a data sample will be displayed rather than the entire dataset. Choose OK to continue.
  13. In the Dimension Mapping section of the Details panel, map the new data columns to your dimension's properties and attributes.
  14. If there are any remaining issues shown in the Mapping Requirements section, resolve them.
  15. If you want to omit validation for specific hierarchies, to allow non-leaf members to contain fact data, click Select hierarchies in the Conditional Validation section of the Details panel, and then select the hierarchies that you want to omit from validation.
    For details about storing data in non-leaf members, see Entering Values with Multiple Hierarchies.
  16. If any cells in the grid appear with red highlighting, those cells have data quality issues, and those rows will be omitted from the model if you don't resolve the issues. Select a highlighted cell to see information about the issue in the Details panel.

    When you select a column or cell, a menu appears, with options for performing transforms. There are two parts to this menu:

    • Choose the Quick Actions option to perform actions such as deleting rows that contain the selected value.
    • Select the (Smart Transformations) icon to list suggested transformations to apply. You can also select Create a Transform to customize a transform in the transformation bar.
  17. Select Finish Mapping.
    A dimension data import job never deletes existing members, but only adds additional ones. For example: You have a dimension with members A, B and C. You trigger a data import job that imports members B, C and D. You'd expect that the dimension would then have members B, C and D, but in fact the dimension has now members A, B, C and D.

Allow Data Import and Model Export with a File Server

The SAP Analytics Cloud agent must be configured in order to allow importing data from a file server or exporting a model to a file server.


The SAP Analytics Cloud agent must be installed. For more information, see Installing SAP Analytics Cloud Agent.

If you have used the SAP Analytics Cloud Agent Simple Deployment Kit to install the SAP Analytics Cloud Agent, you must update the file server import allowlist file following the instructions in the Post-Setup Guide instead of the instructions below.

Data import from file server or model export to file server will assume the file permission level based on the user that started the Tomcat process. For import, read permission is required. For export, write permission is required. The user depends on your Tomcat setup. This may be the Windows system user, a specific user account that started Tomcat as a service in Windows, or the user that executes startup.bat for Windows or for Linux. The system administrator must ensure this user has permissions to access the local share or the network share on a different machine.
Any users under the specific tenant will have access to all files defined within the allowlist.


For importing data, a file server location allowlist must be configured. Only file server paths allowed by this allowlist can be accessed when creating a model from file, or importing data from files.

For exporting models, another file server location allowlist must be configured. Only file server paths allowed by this allowlist can be accessed when exporting a model.


  1. Create an allowlist file as a text document: allowlist.txt.
    Example allowlist.txt:
    The file must follow the following format:
    • The file must be encoded in UTF-8 format.
    • Each line in the file should specify only one allowed path. All descendant paths will be allowed.
    • The folder path is system specific. If the agent is running on a Microsoft web application server, the path should follow Windows format. For example: C:\folder1\folder2 or \\servername\volume\path. If the agent is running on a Linux system, the path should follow Linux format. For example, /net/abc/
    • Multiple lines are allowed.
    Leading, trailing, and empty lines are ignored.
  2. Define the file server allowlist using one of the following methods:
    • Add the allowlist location in your Tomcat JVM properties.

      In the Apache Tomcat GUI tool, go to the Java tab. Under Java Options, add one of these lines:

      • For import data: -DSAP_CLOUD_AGENT_FILE_SERVER_WHITELIST_PATH=<AllowlistFilepath>
      • For export model: -DSAP_CLOUD_AGENT_FILE_SERVER_EXPORT_WHITELIST_PATH=<AllowlistFilepath>

      Alternatively, you can add the allowlist location to JAVA_OPTS. Please refer to the Apache Tomcat guide for detail.

    • Set the operating system environment variable SAP_CLOUD_AGENT_FILE_SERVER_WHITELIST_PATH or SAP_CLOUD_AGENT_FILE_SERVER_EXPORT_WHITELIST_PATH to the location of the allowlist file.

    You must specify the complete path up to and including the allowlist file. For example, C:\<full path to file>\allowlist.txt.


    If you choose to use an environment variable, you must restart Tomcat.

    • If you’re running Tomcat via command line: Shut down the existing Tomcat process, then add the environment variable, and then start Tomcat from a new command line window.
    • If you’re running Tomcat as a Windows service: Restart the Tomcat service by using the Tomcat configuration manager.
  3. Restart the SAP Analytics Cloud agent.
    Updates to the allowlist environment variable will not take effect until the agent is restarted, and after restart, may require up to one minute to take effect.
  4. In SAP Analytics Cloud, go to Start of the navigation path (Main Menu) Next navigation step  System Next navigation step  Administration Next navigation step System ConfigurationEnd of the navigation path.
  5. Select (Edit).
  6. For data import, turn on Allow model import from File Server. For model export, turn on Allow model export to File Server.
  7. Select (Save).
  8. Go to Start of the navigation path (Main Menu) Next navigation step  Connection Next navigation step Connections Next navigation step  (Add Connection) Next navigation step Import Data Connection Next navigation step File ServerEnd of the navigation path.
  9. In the dialog, enter a Connection Name, Description, and the Folder Path.

    The Folder Path should match the path listed in your allowlist file.

  10. Select Create.


The environment variables and allowlist files are polled once a minute.