**Apache Airflow version**:
2.1.0

**What happened**:
There are several hooks that still use optional parameters from the classic `Extra` field.  However, when creating the connection the `Extra` field is overwritten with values from the custom fields that are included in the form.  Because the `Extra` field is overwritten, these optional parameters cannot be used by the hook.

For example, in the `AzureDataFactoryHook`, If `resource_group_name` or `factory_name` are not provided when initializing the hook, it defaults to the value specified in the connection extras. Using the Azure Data Factory connection form, here is the initial connection submission:
![image](https://user-images.githubusercontent.com/48934154/127029091-a8b1c979-f238-4bac-9d3a-f94b6cd92a2b.png)

After saving the connection, the `Extra` field is overwritten with the custom fields that use "extras" under the hood:
![image](https://user-images.githubusercontent.com/48934154/127029242-79c990f0-b9cf-43bb-9a6b-28b4e9c6d4e1.png)


**What you expected to happen**:

Wavering slightly but I would have initially expected that the `Extra` field wasn't overwritten but updated with both the custom field "extras" plus the originally configured values in the `Extra` field.  However, a better UX would be that the values used in the `Extra` field should be separate custom fields for these hooks and the `Extra` field is hidden.  Perhaps it's even both?

**How to reproduce it**:
Install either the Microsoft Azure or Snowflake providers, attempt to create a connection for either the Snowflake, Azure Data Factory, Azure Container Volume, or Azure types with the `Extra` field populated prior to saving the form.


**Anything else we need to know**:
Happy to submit PRs to fix this issue. 🚀 


airflow/www/views.py
x_points[task_instance.task_id].append(date_time)
                y_points[task_instance.task_id].append(float(task_instance.duration))
                fails_dict_key = (task_instance.dag_id, task_instance.task_id, task_instance.execution_date)
                fails_total = fails_totals[fails_dict_key]
                cumulative_y[task_instance.task_id].append(float(task_instance.duration + fails_total))
        
        
        y_unit = infer_time_unit([d for t in y_points.values() for d in t])
        cum_y_unit = infer_time_unit([d for t in cumulative_y.values() for d in t])
        
        chart.create_y_axis('yAxis', format='.02f', custom_format=False, label=f'Duration ({y_unit})')
        chart.axislist['yAxis']['axisLabelDistance'] = '-15'
        cum_chart.create_y_axis('yAxis', format='.02f', custom_format=False, label=f'Duration ({cum_y_unit})')
        cum_chart.axislist['yAxis']['axisLabelDistance'] = '-15'
        for task_id in x_points:
            chart.add_serie(
                name=task_id,
                x=x_points[task_id],
                y=scale_time_units(y_points[task_id], y_unit),
            )
            cum_chart.add_serie(
                name=task_id,
                x=x_points[task_id],
                y=scale_time_units(cumulative_y[task_id], cum_y_unit),
            )
        dates = sorted({ti.execution_date for ti in task_instances})
        max_date = max(ti.execution_date for ti in task_instances) if dates else None
        session.commit()
        form = DateTimeWithNumRunsForm(
            data={