# Jobs overview

### Introduction

The job page provides a comprehensive view of each job, including scheduling options, a list of outputs from the last run, and a detailed history of all runs.

### Accessing the job page

#### From the data flow designer

In the data flow designer, once your data flow is ready, click the **Run** button. This action will either create a new job if it doesn't exist or initiate a run instance for an existing job. When job finishes working, you will see a notification and can access the job's result directly from the notification or by clicking the **Job** button on the toolbar.

#### Direct access

You can access existing jobs by navigating to the **Jobs** section from the Home Screen.

Note: You cannot create a new job directly from the Job page. Jobs are only created through the data flow designer.

### Understanding the job page layout

#### Scheduling

Customize when and how often your job runs. This section allows you to configure recurring schedules or one-time executions.

#### Outputs of the last run

This area displays the results from the most recent execution of the job. Outputs can include reports, charts, or datasets. Click on an output to get a quick preview. 

#### Run monitor

Here, you see a chronological list of every instance the job has run. You can drill down for each run to view detailed information such as status, outputs, and logs. 

### User flow for monitoring a job

**Start a job.** In the data flow designer, click the **Run** button to initiate a job or a new run of an existing job.

**Job creation.** If the job doesn't exist, it will be automatically created.

**Monitoring the job.** Once the job starts, you can go to the Job page.

* View the **status** of the current run.
* Check the **outputs** from the last run.
* Look through the **history** of all runs.

### Tips for effective job management

**Regularly check schedules.** Ensure your jobs are running at the intended times.

**Preview outputs frequently.** Regular previews help in catching errors or anomalies early.

**Review logs.** In case of failures or unexpected results, logs are invaluable for diagnosing issues.

**Update data flows as needed.** Changes in data flows are reflected in subsequent job runs. Keep your flows updated for accurate results.