### 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)

)
            .filter_by(execution_date=dttm, dag_id=dag_id, task_id=task_id, map_index=map_index)
            .one_or_none()
        )
        if ti is None:
            ti_attrs: list[tuple[str, Any]] | None = None
        else:
            ti.refresh_from_task(task)
            ti_attrs_to_skip = [
                "dag_id",
                "key",
                "mark_success_url",
                "log",
                "log_url",
                "task",
                "trigger",
                "triggerer_job",
            ]
            
            with warnings.catch_warnings():
                warnings.simplefilter("ignore", RemovedInAirflow3Warning)
                all_ti_attrs = (
                    (name, getattr(ti, name))
                    for name in dir(ti)
                    if not name.startswith("_") and name not in ti_attrs_to_skip
                )
            ti_attrs = sorted((name, attr) for name, attr in all_ti_attrs if not callable(attr))
        attr_renderers = wwwutils.get_attr_renderer()
        attrs_to_skip = getattr(task, "HIDE_ATTRS_FROM_UI", set())
        def include_task_attrs(attr_name):