Azure Data Factory - traverse JSON array with multiple rows

You can use Data flow activity to get desired result.

First add the REST API source then use select transformer and add required columns.

After this select Derived Column transformer and use unfold function to flatten JSON array.

Another way is to use Flatten formatter.

I tend to use a more ELT pattern for this, ie passing the JSON to a Stored Proc activity and letting the SQL database handle the JSON. This assumes you already have access to a SQL DB which is very capable with JSON.

A simplified example:

DECLARE @json NVARCHAR(MAX) = '{
    "GroupIds": [
        "1234",
        "2345",
        "3456",
        "4567"
    ],
    "Id": "w5a19-a493-bfd4-0a0c8djc05",
    "Name": "Test Item",
    "Description": "test item description",
    "Notes": null,
    "ExternalId": null,
    "ExpiryDate": null,
    "ActiveStatus": 0,
    "TagIds": [
        "784083-4c77-b8fb-0135046c",
        "86de96-44c1-a497-0a308607",
        "7565aa-437f-af36-8f9306c9",
        "d5d841-1762-8c14-d8420da2",
        "bac054-2b6e-a19b-ef5b0b0c"
    ],
    "ResourceIds": []
}'

SELECT
    g.[value] AS groupId,
    m.Id,
    m.[Name]
FROM OPENJSON( @json, '$' )
WITH
    (
    Id          VARCHAR(50) '$.Id',
    [Name]      VARCHAR(50) '$.Name',
    GroupIds    NVARCHAR(MAX) AS JSON
    ) m
    CROSS APPLY OPENJSON( @json, '$.GroupIds' ) g;

You could convert this to a stored procedure where @json is the parameter and convert the SELECT to an INSERT.

My results:

I worked through a very similar example with more screenprints here which is worth a look. It's a different pattern to using Mapping Data Flows but if you already have SQL available then it makes sense to use it rather than fire up separate compute with duplicate cost. If you are not logging to a SQL DB or have access to one, then Mapping Data Flows approach might make sense to you.