### 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.log.debug("Using DatabaseCallbackSink as callback sink.")
                self.executor.callback_sink = DatabaseCallbackSink()
            self.executor.start()
            self.register_signals()
            if self.processor_agent:
                self.processor_agent.start()
            execute_start_time = timezone.utcnow()
            self._run_scheduler_loop()
            if self.processor_agent:
                
                self.processor_agent.terminate()
                
                
                
                if self.processor_agent.all_files_processed:
                    self.log.info(
                        "Deactivating DAGs that haven't been touched since %s", execute_start_time.isoformat()
                    )
                    DAG.deactivate_stale_dags(execute_start_time)
            settings.Session.remove()  
        except Exception:
            self.log.exception("Exception when executing SchedulerJob._run_scheduler_loop")
            raise
        finally:
            try:
                self.executor.end()
            except Exception:
                self.log.exception("Exception when executing Executor.end")
            if self.processor_agent:
                try: