### 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)

tis_to_reset_or_adopt = with_row_locks(
                        query, of=TI, session=session, **skip_locked(session=session)
                    ).all()
                    to_reset = self.executor.try_adopt_task_instances(tis_to_reset_or_adopt)
                    reset_tis_message = []
                    for ti in to_reset:
                        reset_tis_message.append(repr(ti))
                        ti.state = State.NONE
                        ti.queued_by_job_id = None
                    for ti in set(tis_to_reset_or_adopt) - set(to_reset):
                        ti.queued_by_job_id = self.id
                    Stats.incr("scheduler.orphaned_tasks.cleared", len(to_reset))
                    Stats.incr("scheduler.orphaned_tasks.adopted", len(tis_to_reset_or_adopt) - len(to_reset))
                    if to_reset:
                        task_instance_str = "\n\t".join(reset_tis_message)
                        self.log.info(
                            "Reset the following %s orphaned TaskInstances:\n\t%s",
                            len(to_reset),
                            task_instance_str,
                        )
                    
                    
                    session.flush()
                except OperationalError:
                    session.rollback()
                    raise
        return len(to_reset)
    @provide_session
    def check_trigger_timeouts(self, session: Session = NEW_SESSION) -> None: