3. Data Integrations

Finally, we need to configure the data integrations asset, which allows us to connect everything by mapping what data gets ingested as which Dawiso attributes.

Here is the empty dataIntegrations template:

"dataIntegrations": [
    {
        "applicationKey": "app",
        "dataSourceDefinitionKey": "data_source_definition",
        "versionKey": "default",
        "mappings": [
            {
                "queryKey": "",
                "objectTypeKey": "",
                "mapping": [
                    {
                        "fieldKey": "",
                        "attributeTypeKey": ""
                    }
                ]
            },
    }
],

Property	Description
applicationKey	Key of the application we are ingesting the data to.
dataSourceDefinitionKey	Key of the data source definition. A data source definition specifies from where data is ingested and how.
versionKey	Key of the provider version. Usually, the default value is used.
mappings	Array of mappings that assign ingested columns to their corresponding Dawiso attribute types. This is necessary only for attribute types. All columns that are not identifier-based (name, key, parent object key) must be explicitly mapped for correct processing during metadata ingestion.

Mappings

In the mappings property, we can assign all ingested fields (that aren’t identifiers like object names, object keys, etc.) to their appropriate attribute type counterpart. Every mapping has:

• A fieldKey which is the name of the column in your database and
• An attributetypeKey which is the corresponding attribute type in Dawiso.

In the example package, the Recipe

TABLE_NAME	COLUMN_NAME	Field Type
Recipe	RecipeID	Object key (Identifier)
Recipe	CuisineID	Parent key (Identifier)
Recipe	Name	Name (Identifier)
Recipe	Description	Attribute (core_description_scanned)
Recipe	Difficulty	Attribute  (difficulty)
Recipe	LastMade	Attribute  (recipe_last_made)

"mappings": [
    {
        "queryKey": "recipe",
        "objectTypeKey": "recipe",
        "mapping": [
            {
                "fieldKey": "Description",
                "attributeTypeKey": "core_description_scanned"
            },
            {
                "fieldKey": "LastMade",
                "attributeTypeKey": "recipe_last_made"
            },
            {
                "fieldKey": "Difficulty",
                "attributeTypeKey": "difficulty"
            }
        ]
    },
    …
]

Save and Install the Package

Once you are done, Save the package and Install it. Now you can create your new data source.