### 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)

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        data_dag_states = [
            {
                
                
                "date": dr.date if isinstance(dr.date, str) else dr.date.isoformat(),
                "state": dr.state,
                "count": dr.count,
            }
            for dr in dag_states
        ]
        if dag_states and dag_states[-1].data_interval_start and dag_states[-1].data_interval_end:
            last_automated_data_interval = DataInterval(
                timezone.coerce_datetime(dag_states[-1].data_interval_start),
                timezone.coerce_datetime(dag_states[-1].data_interval_end),
            )
            year = last_automated_data_interval.end.year
            restriction = TimeRestriction(dag.start_date, dag.end_date, False)
            dates = collections.Counter()
            if isinstance(dag.timetable, CronMixin):
                
                dates_iter: Iterator[datetime | None] = croniter(
                    dag.timetable._expression,
                    start_time=last_automated_data_interval.end,
                    ret_type=datetime,
                )
                for dt in dates_iter:
                    if dt is None:
                        break
                    if dt.year != year: