### Description

At the moment the Azure Data Factory hook only supports `TokenCredential` (service principal client ID and secret). It would be very useful to have support for other authentication types like managed identity. Preferably, we would create a `DefaultTokenCredential` if the client ID and secret are not provided in the connection.

### Use case/motivation

We're using Airflow on Azure Kubernetes Service and this would allow us to use the pod identity for authentication which is a lot cleaner than creating a service principal.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/providers/microsoft/azure/hooks/data_factory.py
self,
        dataset_name: str,
        resource_group_name: Optional[str] = None,
        factory_name: Optional[str] = None,
        **config: Any,
    ) -> DatasetResource:
        """
        Get the dataset.
        :param dataset_name: The dataset name.
        :param resource_group_name: The resource group name.
        :param factory_name: The factory name.
        :param config: Extra parameters for the ADF client.
        :return: The dataset.
        """
        return self.get_conn().datasets.get(resource_group_name, factory_name, dataset_name, **config)
    def _dataset_exists(self, resource_group_name, factory_name, dataset_name) -> bool:
        """Return whether or not the dataset already exists."""
        datasets = {
            dataset.name
            for dataset in self.get_conn().datasets.list_by_factory(resource_group_name, factory_name)
        }
        return dataset_name in datasets
    @provide_targeted_factory
    def update_dataset(