### 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)

"""
    Cast the task_duration to an int was for optimization for large/huge dags if task_duration > 10s
    otherwise we keep it as a float with 3dp
    """
    return int(task_duration) if task_duration > 10.0 else round(task_duration, 3)
def sanitize_args(args: dict[str, str]) -> dict[str, str]:
    """
    Remove all parameters starting with `_`
    :param args: arguments of request
    :return: copy of the dictionary passed as input with args starting with `_` removed.
    """
    return {key: value for key, value in args.items() if not key.startswith("_")}
def get_safe_url(url):
    """Given a user-supplied URL, ensure it points to our web server"""
    if not url:
        return url_for("Airflow.index")
    
    
    if ";" in unquote(url):
        return url_for("Airflow.index")
    host_url = urlsplit(request.host_url)
    redirect_url = urlsplit(urljoin(request.host_url, url))
    if not (redirect_url.scheme in ("http", "https") and host_url.netloc == redirect_url.netloc):
        return url_for("Airflow.index")
    
    return redirect_url.geturl()
def get_date_time_num_runs_dag_runs_form_data(www_request, session, dag):