### 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)

end_date = task_dict["end_date"] or timezone.utcnow()
            task_dict["end_date"] = end_date
            task_dict["start_date"] = task_dict["start_date"] or end_date
            task_dict["state"] = State.FAILED
            task_dict["operator"] = task.operator_name
            task_dict["try_number"] = try_count
            task_dict["extraLinks"] = task.extra_links
            task_dict["execution_date"] = dttm.isoformat()
            task_dict["run_id"] = dag_run_id
            tasks.append(task_dict)
        task_names = [ti.task_id for ti in tis]
        data = {
            "taskNames": task_names,
            "tasks": tasks,
            "height": len(task_names) * 25 + 25,
        }
        session.commit()
        return self.render_template(
            "airflow/gantt.html",
            dag=dag,
            dag_run_id=dag_run_id,
            execution_date=dttm.isoformat(),
            form=form,
            data=data,
            base_date="",
            root=root,
            dag_model=dag_model,
        )
    @expose("/extra_links")
    @auth.has_access(