### 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)

models.DagModel.get_dagmodel(dag_id).set_is_paused(is_paused=False)
        try:
            dag.create_dagrun(
                run_type=DagRunType.MANUAL,
                execution_date=execution_date,
                data_interval=dag.timetable.infer_manual_data_interval(run_after=execution_date),
                state=State.QUEUED,
                conf=run_conf,
                external_trigger=True,
                dag_hash=get_airflow_app().dag_bag.dags_hash.get(dag_id),
                run_id=run_id,
            )
        except (ValueError, ParamValidationError) as ve:
            flash(f"{ve}", "error")
            form = DateTimeForm(data={"execution_date": execution_date})
            
            for k, v in form_fields.items():
                form_fields[k]["value"] = run_conf[k]
            return self.render_template(
                "airflow/trigger.html",
                form_fields=form_fields,
                dag_id=dag_id,
                origin=origin,
                conf=request_conf,
                form=form,
                is_dag_run_conf_overrides_params=is_dag_run_conf_overrides_params,
            )
        flash(f"Triggered {dag_id}, it should start any moment now.")
        return redirect(origin)
    def _clear_dag_tis(