dss-visual-edit

Building a complete application to test with end-users

As a first step, make sure to read the How to Use guide on the plugin’s presentation page.

Integrating edits in automation Scenarios

We recommend creating the following automation Scenarios:

• Commit Edits, to build all datasets downstream of the editlog and to update dashboards based on them. Remember that edits made via the webapp are not instantly reflected in the edits and edited datasets (only the editlog is updated in real-time).
  • Its execution can be scheduled, or it can be triggered manually. If you have a Reset Edits scenario, add a step at the end to also run the Commit Edits scenario.
  • If you want to allow end-users to trigger this scenario on their own, you can embed the Visual Edit webapp in a Dashboard to which you will add a Scenario tile (more on this in the next section).
• Update Source, to take into account any changes or additional data from source systems, re-build the Original Dataset used by the webapp, and re-run the Commit Edits scenario.

Publishing the webapp to a Dashboard

The best way to make the webapp accessible to business users is by publishing it to a Dashboard. There can be 2 separate Dashboards for Editing and for Reporting purposes, or there can be a single Dashboard with 2 pages.

• Editing Dashboard:
  • From the Webapp view, click on the ACTIONS button of the menu in the top-right corner, to publish the webapp to a Dashboard.
  • From the Dashboard view, add other “tiles” to the page, such as a Text tile with instructions on how to use the webapp, and a Scenario tile displayed as a button to run the Commit Edits Scenario discussed above. You can also adjust the layout.
• Reporting Dashboard:
  • This would consist in charts built from the edited dataset or other datasets downstream.
  • It could include a Scenario tile to run the Update Source Scenario.
  • It would be accessed by business users via the web, and it could also be scheduled to be converted to a PDF and sent by email via a Scenario.

Important remarks on deployment:

• This Dashboard and its associated link would only be for test purposes.
  • Because you’re building a project with an interface where users can enter data which then gets processed, you’ll need to have two instances of the project: one for development and one for production; each will have its own set of edits.
  • You can reset edits by creating and running a Reset Edits scenario with an Initialize editlog Step. This type of Scenario Step is provided by the plugin and can be found toward the end of the list of available Steps. Only use this on a design node as part of your tests.
  • Once your tests are successful, the next step is to deploy your project on an automation node, or as a duplicate project on your design node.
• End-users must be Dataiku users on a Reader license or above.