**Apache Airflow version**: 1.10.*
**BackPort Packages version**: 2020.10.5rc1

**What happened**:

`BigQueryInsertJobOperator` tries to start a BigQuery job by specifying a job_id which is a combination of `dag_id`, `task_id`, `execution_date` and an additional `uniqueness_suffix`.

https://github.com/apache/airflow/blob/master/airflow/providers/google/cloud/operators/bigquery.py#L2072

However, because BigQuery only accepts alphanumeric (in additon to dashes and underscore) characters then, if a DagID contains a version number whcih includes a `.` character then this will cause the task to fail.

https://cloud.google.com/bigquery/docs/running-jobs#generate-jobid

**How to reproduce it**:
Create a DAG with the name `my-dag-v1.0`.
airflow/providers/google/cloud/hooks/bigquery.py
and then passing it to ``update_dataset`` will ensure that the changes
        will only be saved if no modifications to the dataset occurred
        since the read.
        :param dataset_resource: Dataset resource that will be provided
            in request body.
            https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets#resource
        :type dataset_resource: dict
        :param dataset_id: The id of the dataset.
        :type dataset_id: str
        :param fields: The properties of ``dataset`` to change (e.g. "friendly_name").
        :type fields: Sequence[str]
        :param project_id: The Google Cloud Project ID
        :type project_id: str
        :param retry: How to retry the RPC.
        :type retry: google.api_core.retry.Retry
        """
        dataset_resource["datasetReference"] = dataset_resource.get("datasetReference", {})
        for key, value in zip(["datasetId", "projectId"], [dataset_id, project_id]):
            spec_value = dataset_resource["datasetReference"].get(key)
            if value and not spec_value:
                dataset_resource["datasetReference"][key] = value
        self.log.info('Start updating dataset')
        dataset = self.get_client(project_id=project_id).update_dataset(
            dataset=Dataset.from_api_repr(dataset_resource),
            fields=fields,
            retry=retry,
        )
        self.log.info("Dataset successfully updated: %s", dataset)
        return dataset
    def patch_dataset(