### Apache Airflow version

main (development)

### What happened

1. When not providing `project_id` to `BigQueryGetDataOperator` in deferrable mode (`project_id=None`), the query generated by `generate_query` method is bugged, i.e.,: 

````sql
from `None.DATASET.TABLE_ID` limit ...
````

2. `as_dict` param does not work `BigQueryGetDataOperator`.

### What you think should happen instead

1. When `project_id` is `None` - it should be removed from the query along with the trailing dot, i.e.,:

````sql
from `DATASET.TABLE_ID` limit ...
````

2. `as_dict` should be added to the serialization method of `BigQueryGetDataTrigger`.

### How to reproduce

1. Create a DAG file with `BigQueryGetDataOperator` defined as follows:
```python
BigQueryGetDataOperator(
        task_id="bq_get_data_op",
        # project_id="PROJECT_ID",  <-- Not provided
        dataset_id="DATASET",
        table_id="TABLE",
        use_legacy_sql=False,
        deferrable=True
    )
````

2. 1. Create a DAG file with `BigQueryGetDataOperator` defined as follows:
```python
BigQueryGetDataOperator(
        task_id="bq_get_data_op",
        project_id="PROJECT_ID",
        dataset_id="DATASET",
        table_id="TABLE",
        use_legacy_sql=False,
        deferrable=True,
        as_dict=True
    )
````

### Operating System

Debian

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

The `generate_query` method is not unit tested (which would have prevented it in the first place) - will be better to add one.

### Are you willing to submit 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)

)
            BigQueryTableLink.persist(
                context=context,
                task_instance=self,
                dataset_id=table.to_api_repr()["tableReference"]["datasetId"],
                project_id=table.to_api_repr()["tableReference"]["projectId"],
                table_id=table.to_api_repr()["tableReference"]["tableId"],
            )
            return
        if not self.schema_fields and self.schema_object and self.source_format != "DATASTORE_BACKUP":
            gcs_hook = GCSHook(
                gcp_conn_id=self.google_cloud_storage_conn_id,
                impersonation_chain=self.impersonation_chain,
            )
            schema_fields = json.loads(
                gcs_hook.download(self.gcs_schema_bucket, self.schema_object).decode("utf-8")
            )
        else:
            schema_fields = self.schema_fields
        source_uris = [f"gs://{self.bucket}/{source_object}" for source_object in self.source_objects]
        project_id, dataset_id, table_id = bq_hook.split_tablename(
            table_input=self.destination_project_dataset_table,
            default_project_id=bq_hook.project_id or "",
        )
        table_resource = {
            "tableReference": {
                "projectId": project_id,
                "datasetId": dataset_id,
                "tableId": table_id,
            },