### 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)

if is_lock_not_available_error(error=e):
                        self.log.debug("Critical section lock held by another Scheduler")
                        Stats.incr("scheduler.critical_section_busy")
                        session.rollback()
                        return 0
                    raise
            guard.commit()
        return num_queued_tis
    @retry_db_transaction
    def _get_next_dagruns_to_examine(self, state: DagRunState, session: Session):
        """Get Next DagRuns to Examine with retries."""
        return DagRun.next_dagruns_to_examine(state, session)
    @retry_db_transaction
    def _create_dagruns_for_dags(self, guard: CommitProhibitorGuard, session: Session) -> None:
        """Find Dag Models needing DagRuns and Create Dag Runs with retries in case of OperationalError."""
        query, dataset_triggered_dag_info = DagModel.dags_needing_dagruns(session)
        all_dags_needing_dag_runs = set(query.all())
        dataset_triggered_dags = [
            dag for dag in all_dags_needing_dag_runs if dag.dag_id in dataset_triggered_dag_info
        ]
        non_dataset_dags = all_dags_needing_dag_runs.difference(dataset_triggered_dags)
        self._create_dag_runs(non_dataset_dags, session)
        if dataset_triggered_dags:
            self._create_dag_runs_dataset_triggered(
                dataset_triggered_dags, dataset_triggered_dag_info, session
            )
        
        guard.commit()
        
    def _create_dag_runs(self, dag_models: Collection[DagModel], session: Session) -> None: