### Description

Add listeners for Datasets (events)

### Use case/motivation

As Airflow administrators, we would like to trigger some external processes based on all datasets being created/updated by our users. We came across the listeners for the dag runs and task instances (which are also useful), but are still missing listeners for 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)

from airflow.timetables.interval import _DataIntervalTimetable
        warnings.warn(
            "`DAG.previous_schedule()` is deprecated.",
            category=RemovedInAirflow3Warning,
            stacklevel=2,
        )
        if not isinstance(self.timetable, _DataIntervalTimetable):
            return None
        return self.timetable._get_prev(timezone.coerce_datetime(dttm))
    def get_next_data_interval(self, dag_model: DagModel) -> DataInterval | None:
        """Get the data interval of the next scheduled run.
        For compatibility, this method infers the data interval from the DAG's
        schedule if the run does not have an explicit one set, which is possible
        for runs created prior to AIP-39.
        This function is private to Airflow core and should not be depended on as a
        part of the Python API.
        :meta private:
        """
        if self.dag_id != dag_model.dag_id:
            raise ValueError(f"Arguments refer to different DAGs: {self.dag_id} != {dag_model.dag_id}")
        if dag_model.next_dagrun is None:  
            return None
        data_interval = dag_model.next_dagrun_data_interval
        if data_interval is not None:
            return data_interval
        
        
        
        return self.infer_automated_data_interval(dag_model.next_dagrun)
    def get_run_data_interval(self, run: DagRun | DagRunPydantic) -> DataInterval: