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Creating an Advanced Analytic connection

Advanced Analytic connections are created in Data load editor and Script editor.

Once you have created a connection you can select data from the available tables to send to the model for machine learning problems and tasks, and then load the results into your app. The connection can not only be used in your data load script, but also in chart expressions to call deployed model endpoints and enable interactive charts using machine learning insights.

You must know the settings and access credentials to the service that you want to connect to.

Configurable settings

The following settings can be configured in the connection dialog:

Configurable settings in the connection dialog
Field Description
URL

Host URL to the platform where the model is deployed.
Method

HTTP method to use in the API endpoint requests to the model.

  • GET

  • POST

Content Type

HTTP request header Content-Type.

For example “application/json”.
HTTP Headers

HTTP headers fields, such as Name and Value, to send in every API endpoint requests to the model.
Query Parameters

Query parameters, such as Name and Value, that will be attached to the end of the URL.
Authorization Method

The authorization method to be set in the HTTP Authorization request header in order to authenticate the user.

Supported authorization methods:

  • None

  • Bearer Token

  • AWS Auth v4 Signature
Request

  • Field Formats: Field formats can be optionally added and specified including Name and Value.

  • Timestamp Format: Timestamp format needs to be changed if the default format does not fit the format used by the model.
Response Fields

  • Load all available fields: Enable loading of all available fields returned by the machine learning endpoint. Disabling this, lets you to specify the table fields and values to load into the app.

    When developing apps, it is recommended to first load all fields returned from the model endpoint, and then potentially remove the fields that are not needed for the analysis in the app.
Response Table

  • Table Fields (JMESPath): The Table fields can be specified by adding:

    • Name: the name of the table that will be loaded in the app.

    • Value: the name of the response row in the JSON response array.

    JMESPath query language can be used to parse the JSON response array.
Association

  • Association field: A field from the input data table containing a unique identifier.

    It is required to include this field in the source data when making an endpoint request for the results table returned to be associated with the source field table using a key. The designated field will be returned as a field in the response and enable the predictions to be associated with the source data in the data model. This can be any field with a unique ID, either from the source data or as part of the table load process.

  • Send Association Field: When selected, the field specified as the association field will be both returned to Qlik Sense and included in the fields sent to the endpoint

    If the field belongs to the source data and is expected by the model, it needs to be sent to the model by enabling Send Association Field.
Name The name of the connection. The default name will be used if you do not enter a name.

Creating a new connection

Do the following:

  1. Access the connector through Data load editor or Script editor.

    Click Create new connection and select the Advanced Analytic option from the list.

  2. Fill out the connection dialog fields.

  3. Click Create.

Your connection is now listed under Data connections in the Data load editor.

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