### Apache Airflow version

2.4.1

### What happened

When using dataset scheduling, it isn't obvious which datasets a downstream dataset consumer is awaiting in order for the DAG to be scheduled.

I would assume that this is supposed to be solved by the `Latest Update` column in the modal that opens when selecting `x of y datasets updated`, but it appears that the data isn't being populated.

<img width="601" alt="image" src="https://user-images.githubusercontent.com/5778047/194116186-d582cede-c778-47f7-8341-fc13a69a2358.png">

Although one of the datasets has been produced, there is no data in the `Latest Update` column of the modal.

In the above example, both datasets have been produced > 1 time.

<img width="581" alt="image" src="https://user-images.githubusercontent.com/5778047/194116368-ceff241f-a623-4893-beb7-637b821c4b53.png">

<img width="581" alt="image" src="https://user-images.githubusercontent.com/5778047/194116410-19045f5a-8400-47b0-afcb-9fbbffca26ee.png">


### What you think should happen instead

The `Latest Update` column should be populated with the latest update timestamp for each dataset required to schedule a downstream, dataset consuming DAG.

Ideally there would be some form of highlighting on the "missing" datasets for quick visual feedback when DAGs have a large number of datasets required for scheduling.

### How to reproduce

1. Create a DAG (or 2 individual DAGs) that produces 2 datasets
2. Produce both datasets
3. Then produce _only one_ dataset
4. Check the modal by clicking from the home screen on the `x of y datasets updated` button.

### Operating System

Debian GNU/Linux 11 (bullseye)

### Versions of Apache Airflow Providers

_No response_

### Deployment

Docker-Compose

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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)

num_of_all_dags = status_count_paused
            else:
                current_dags = all_dags
                num_of_all_dags = all_dags_count
            sort_column = DagModel.__table__.c.get(arg_sorting_key)
            if sort_column is not None:
                if arg_sorting_direction == "desc":
                    sort_column = sort_column.desc()
                current_dags = current_dags.order_by(sort_column)
            dags = current_dags.options(joinedload(DagModel.tags)).offset(start).limit(dags_per_page).all()
            user_permissions = g.user.perms
            can_create_dag_run = (
                permissions.ACTION_CAN_CREATE,
                permissions.RESOURCE_DAG_RUN,
            ) in user_permissions
            dataset_triggered_dag_ids = {dag.dag_id for dag in dags if dag.schedule_interval == "Dataset"}
            if dataset_triggered_dag_ids:
                dataset_triggered_next_run_info = get_dataset_triggered_next_run_info(
                    dataset_triggered_dag_ids, session=session
                )
            else:
                dataset_triggered_next_run_info = {}
            for dag in dags:
                dag.can_edit = get_airflow_app().appbuilder.sm.can_edit_dag(dag.dag_id, g.user)
                dag.can_trigger = dag.can_edit and can_create_dag_run
                dag.can_delete = get_airflow_app().appbuilder.sm.can_delete_dag(dag.dag_id, g.user)
            dagtags = session.query(func.distinct(DagTag.name)).all()
            tags = [
                {"name": name, "selected": bool(arg_tags_filter and name in arg_tags_filter)}
                for name, in dagtags