### Description

A count of datasets that are currently registered/declared in an Airflow deployment.

### Use case/motivation

Would be nice to see how deployments are adopting datasets.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] 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)

self,
        dag_models: Collection[DagModel],
        dataset_triggered_dag_info: dict[str, tuple[datetime, datetime]],
        session: Session,
    ) -> None:
        """For DAGs that are triggered by datasets, create dag runs."""
        
        
        
        
        exec_dates = {
            dag_id: timezone.coerce_datetime(last_time)
            for dag_id, (_, last_time) in dataset_triggered_dag_info.items()
        }
        existing_dagruns: set[tuple[str, timezone.DateTime]] = set(
            session.query(DagRun.dag_id, DagRun.execution_date).filter(
                tuple_in_condition((DagRun.dag_id, DagRun.execution_date), exec_dates.items())
            )
        )
        for dag_model in dag_models: