### 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)

dag = self.dagbag.get_dag(dag_model.dag_id, session=session)
            if not dag:
                self.log.error("DAG '%s' not found in serialized_dag table", dag_model.dag_id)
                continue
            if not isinstance(dag.timetable, DatasetTriggeredTimetable):
                self.log.error(
                    "DAG '%s' was dataset-scheduled, but didn't have a DatasetTriggeredTimetable!",
                    dag_model.dag_id,
                )
                continue
            dag_hash = self.dagbag.dags_hash.get(dag.dag_id)
            
            
            
            
            
            
            
            
            exec_date = exec_dates[dag.dag_id]
            if (dag.dag_id, exec_date) not in existing_dagruns:
                previous_dag_run = (
                    session.query(DagRun)
                    .filter(
                        DagRun.dag_id == dag.dag_id,
                        DagRun.execution_date < exec_date,
                        DagRun.run_type == DagRunType.DATASET_TRIGGERED,
                    )
                    .order_by(DagRun.execution_date.desc())
                    .first()