### 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)

state=DagRunState.QUEUED,
                    external_trigger=False,
                    session=session,
                    dag_hash=dag_hash,
                    creating_job_id=self.id,
                )
                dag_run.consumed_dataset_events.extend(dataset_events)
                session.query(DatasetDagRunQueue).filter(
                    DatasetDagRunQueue.target_dag_id == dag_run.dag_id
                ).delete()
    def _should_update_dag_next_dagruns(self, dag, dag_model: DagModel, total_active_runs: int) -> bool:
        """Check if the dag's next_dagruns_create_after should be updated."""
        if total_active_runs >= dag.max_active_runs:
            self.log.info(
                "DAG %s is at (or above) max_active_runs (%d of %d), not creating any more runs",
                dag_model.dag_id,
                total_active_runs,
                dag.max_active_runs,
            )
            dag_model.next_dagrun_create_after = None
            return False
        return True
    def _start_queued_dagruns(self, session: Session) -> None:
        """Find DagRuns in queued state and decide moving them to running state."""
        dag_runs = self._get_next_dagruns_to_examine(DagRunState.QUEUED, session)
        active_runs_of_dags = defaultdict(
            int,
            DagRun.active_runs_of_dags((dr.dag_id for dr in dag_runs), only_running=True, session=session),
        )
        def _update_state(dag: DAG, dag_run: DagRun):