Exporting and importing data pipelines

You can export a data pipeline project to a JSON file that contains everything required to reconstruct the data project. The exported JSON file can be imported to the same tenant, or to another tenant. You can use this, for example, to move data projects from one tenant to another, or to make backup copies of data projects. You can also update a data project from a JSON export file.

Exporting a data project

• In Data Integration > Projects, click on the project to export, and select Export.

The project is exported to a JSON file with a file name that consists of the project name, the data platform, and a timestamp.

Importing projects

This section covers importing projects. You can import a cloud data warehouse project or a Qlik Cloud (via Amazon S3) project.

Importing a cloud data warehouse project

You can import an exported cloud data warehouse project to the same tenant it was exported from, or to another tenant. When the project is imported into a tenant other than the original data project's tenant, you need to define new connections for the project, the staging area and for all data sources.

You can change which data platform to use, but it is not possible to change data platform from a cloud data warehouse to Qlik Cloud.

1. In Data Integration > Projects, click in the top right and select Import project.

2. Add the project JSON file. You can either drop it on the dialog, or browse to select the file.

3. Name

   Change the name of the project. The default name is the original project name prefixed with Imported_.

4. Space
   Select which space to add the project to.

5. Description
   Add or edit the description of the project.

6. Data platform

   You can change the data platform of the project.

7. Data connection

   You can change the connection to the data platform.

   This is required if you imported a project from another tenant, or if you changed the data platform in the previous step.

8. Connection to staging area

   You can change the connection to the staging area.

   This is required if you imported a project from another tenant, or in some cases if you changed the data platform in the previous step.

   Information noteThis is not required if the data platform is Snowflake.

9. Replace imported source connections
   You can replace the imported source connections.

   This is required if you imported a project from another tenant.

10. Data schemas prefix

    You can add a prefix to the data schemas that are created in the project. This is useful when the imported project is in the same cloud data warehouse as the exported project.

11. Replace imported source databases and schemas

    You can replace the source schema for landing tasks, and the source database and schema for registered data.

    Select a task and replace the values in New schema and New database.

12. Default database names

    If the data platform is Snowflake or Microsoft Azure Synapse Analytics, you can change default database names.

13. Default warehouse names

    If the data platform is Snowflake, you can change default warehouse names.

14. When you are ready, click Upload.

The project is added to Data Integration home.

Importing a project with Qlik Cloud as data platform

You can import an exported Qlik Cloud (via Amazon S3) project to the same tenant it was exported from, or to another tenant. When the project is imported into a tenant other than the original data project's tenant, you need to define new connections for the project, the staging area and for all data sources.

It is not possible to change data platform from Qlik Cloud to a cloud data warehouse, such as Snowflake.

1. In Data Integration > Projects, click in the top right and select Import project.

2. Add the project JSON file. You can either drop it on the dialog, or browse to select the file.

3. Name

   Change the name of the project. The default name is the original project name prefixed with Imported_.

4. Space
   Select which space to add the project to.

5. Description
   Add or edit the description of the project.

6. Store QVD files in:

   Select where to generate QVD files.

   • Qlik managed storage

   • Customer managed storage

     Amazon S3 storage managed by you.

7. Data connection

   If you selected Customer managed storage, you can change the connection to the Amazon S3 storage area.

   This is required if you imported a project from another tenant.

8. Connection to staging area

   You can change the connection to the Amazon S3 staging area.

   This is required if you imported a project from another tenant, or in some cases if you changed the data platform in the previous step.

9. Replace imported source connections
   You can replace the imported source connections.

   This is required if you imported a project from another tenant.

10. When you are ready, click Upload.

The project is added to Data Integration home.

Updating a project

You can update a project from a JSON export file. This will replace all tasks in the data pipeline, but connections and settings will not be replaced. Data tasks that are not included in the imported project will be removed.

For example, you can import a project exported from the development data space into a project in the production data space to update the production project.

Before you start updating the project:

• If you want a backup of the project before you update, export it by clicking , and then Export.

• You must stop all tasks that will be removed from the data pipeline before you update the project.

• If the project uses SaaS application connections that do not exist yet, you must create the connections and generate metadata before you start importing.

• Make sure that the imported project uses the same cloud data platform, for example, Snowflake.

To update a project:

1. Open the project that you want to update.

2. Click , and then click Import.

3. Select or drop the JSON file that you want to import.

4. Make any required changes for mapping connections that are different between the project and the imported project.

   For example, the imported project could be using a source connection named SQL1, while this project uses a similar connection named SQL2. In this case, map the imported connection to SQL2 in Replace imported source connections.

   Information noteWhen selecting a connection to map, you can create a new database connection, but not a SaaS application connection.

   Click Import when you are ready.

The project is now updated according to the imported JSON file. You may need to validate and sync data tasks that have been updated through the import.