### 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)

timers.call_regular_interval(
            conf.getfloat("scheduler", "pool_metrics_interval", fallback=5.0),
            self._emit_pool_metrics,
        )
        timers.call_regular_interval(
            conf.getfloat("scheduler", "zombie_detection_interval", fallback=10.0),
            self._find_zombies,
        )
        timers.call_regular_interval(60.0, self._update_dag_run_state_for_paused_dags)
        timers.call_regular_interval(
            conf.getfloat("scheduler", "parsing_cleanup_interval"),
            self._orphan_unreferenced_datasets,
        )
        if self._standalone_dag_processor:
            timers.call_regular_interval(
                conf.getfloat("scheduler", "parsing_cleanup_interval"),
                self._cleanup_stale_dags,
            )
        for loop_count in itertools.count(start=1):
            with Stats.timer("scheduler.scheduler_loop_duration") as timer:
                if self.using_sqlite and self.processor_agent:
                    self.processor_agent.run_single_parsing_loop()
                    
                    
                    self.log.debug("Waiting for processors to finish since we're using sqlite")
                    self.processor_agent.wait_until_finished()
                with create_session() as session:
                    num_queued_tis = self._do_scheduling(session)
                    self.executor.heartbeat()
                    session.expunge_all()