### 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)

if not dag_run_id:
            return {"status": "error", "message": "Invalid dag_run_id"}
        dag = get_airflow_app().dag_bag.get_dag(dag_id)
        if not dag:
            return {"status": "error", "message": f"Cannot find DAG: {dag_id}"}
        set_dag_run_state_to_queued(dag=dag, run_id=dag_run_id, commit=confirmed)
        if confirmed:
            return {"status": "success", "message": "Marked the DagRun as queued."}
        else:
            
            all_task_ids = [task.task_id for task in dag.tasks]
            existing_tis = session.query(TaskInstance.task_id).filter(
                TaskInstance.dag_id == dag.dag_id,
                TaskInstance.run_id == dag_run_id,
            )
            completed_tis_ids = [task_id for task_id, in existing_tis]
            tasks_with_no_state = list(set(all_task_ids) - set(completed_tis_ids))
            details = [str(t) for t in tasks_with_no_state]
            return htmlsafe_json_dumps(details, separators=(",", ":"))
    @expose("/dagrun_failed", methods=["POST"])
    @auth.has_access(
        [
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG_RUN),
        ]
    )
    @action_logging
    def dagrun_failed(self):