### 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_run: DagRun,
        session: Session,
    ) -> DagCallbackRequest | None:
        """
        Make scheduling decisions about an individual dag run.
        :param dag_run: The DagRun to schedule
        :return: Callback that needs to be executed
        """
        callback: DagCallbackRequest | None = None
        dag = dag_run.dag = self.dagbag.get_dag(dag_run.dag_id, session=session)
        if not dag:
            self.log.error("Couldn't find dag %s in DagBag/DB!", dag_run.dag_id)
            return callback
        dag_model = DM.get_dagmodel(dag.dag_id, session)
        if (
            dag_run.start_date
            and dag.dagrun_timeout
            and dag_run.start_date < timezone.utcnow() - dag.dagrun_timeout
        ):
            dag_run.set_state(DagRunState.FAILED)
            unfinished_task_instances = (
                session.query(TI)