> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zwiron.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Platform Analytics

> Cross-pipeline analytics for Zwiron job health, throughput, success rates, and historical trends.

The **Analytics** page gives you a bird's-eye view of your entire data platform — how many pipelines are running, how many succeeded or failed today, and how that has changed over time.

Access it from the main navigation under **Analytics**.

***

## Time ranges

All metrics on the Analytics page are filterable by time range:

| Range            | Description                                  |
| ---------------- | -------------------------------------------- |
| **Last 7 days**  | Default view — good for weekly health checks |
| **Last 30 days** | Month-over-month comparison                  |
| **Last 90 days** | Quarterly trend analysis                     |
| **All time**     | Full historical view from account creation   |

***

## Summary cards

At the top of the page, four cards give you the current state at a glance:

| Card          | What it shows                                          |
| ------------- | ------------------------------------------------------ |
| **Running**   | Jobs currently in progress                             |
| **Completed** | Jobs that finished successfully in the selected period |
| **Failed**    | Jobs that ended with failures in the selected period   |
| **Pending**   | Jobs queued but not yet started                        |

***

## Trend chart

The trend chart shows **jobs completed per day** over the selected period. Use this to spot:

* Unusual spikes (more jobs than normal — was a batch load triggered?)
* Gaps (were there days with no successful runs?)
* Growing or shrinking data volume

***

## Status distribution

A donut chart shows the **breakdown by status** for the selected period:

* Completed (green)
* Failed (red)
* Cancelled (grey)

A high failure rate signals systematic problems — credentials expired, source unreachable, schema drift.

***

## Per-job breakdown

Below the aggregate charts, a table lists each job with its run count, success rate, average duration, and last run status for the selected period. Sort by failure rate to find the most problematic pipelines.

***

## Using analytics for on-call

A common workflow is to check Analytics first thing in the morning:

1. Any red cards? → Check failed jobs, see which tables failed, check [Events](/pipelines/events) for error details
2. Trend chart dip? → Were any jobs paused or deleted?
3. Completed count unusual? → Check if a scheduled job didn't trigger

Set up a [Notification](/platform/notifications) for `job_failed` events (in-app or email) so you don't need to check manually. Outbound [webhooks](/platform/webhooks) are coming soon.