# Data Overview

Bugsnag exposes data across error monitoring, team management, and release tracking. Through Coupler.io, you can export any of these entities and combine them to build a complete picture of your application's stability.

## Entities and what they contain

| Entity                         | What you get                                                                      |
| ------------------------------ | --------------------------------------------------------------------------------- |
| Organizations                  | Organization ID, name, slug, billing plan, creation date                          |
| Projects                       | Project name, type, API key, language, error count, URL                           |
| Errors                         | Error class, message, severity, status, first/last seen timestamps, event count   |
| Events                         | Full event payload — stack trace, device info, user info, breadcrumbs, timestamps |
| Pivots                         | Aggregated breakdowns of error data by dimension (browser, OS, app version, etc.) |
| Releases                       | App version, release stage, build tool, source map status, release timestamp      |
| Saved searches                 | Search name, query filters, associated project                                    |
| Saved searches usage summaries | Search ID, query count, last used timestamp                                       |
| Collaborators                  | User name, email, role, two-factor status, project membership                     |
| Teams                          | Team name, ID, project assignments, member count                                  |
| Event fields                   | Custom field names and values attached to error events                            |
| Trace fields                   | Custom field names and values for trace-level data                                |
| Supported integrations         | Integration name, type, configuration status                                      |

## Key metrics and dimensions

#### Error-level metrics

| Metric      | Description                                                 |
| ----------- | ----------------------------------------------------------- |
| Event count | Total number of times an error has occurred                 |
| User count  | Number of unique users affected by an error                 |
| First seen  | Timestamp when the error was first captured                 |
| Last seen   | Timestamp of the most recent occurrence                     |
| Severity    | Error severity level (error, warning, info)                 |
| Status      | Current status of the error (open, fixed, ignored, snoozed) |

#### Event-level dimensions

| Dimension              | Description                                                |
| ---------------------- | ---------------------------------------------------------- |
| App version            | The release version of the app when the event occurred     |
| Release stage          | Environment label (production, staging, development, etc.) |
| OS name / version      | Operating system of the affected device or browser         |
| Browser name / version | Browser context for web errors                             |
| Country                | Country associated with the user session                   |
| User ID / email        | Identifies which user experienced the event                |
| Timestamp              | Exact date and time the event was captured                 |

#### Release metrics

| Metric               | Description                                        |
| -------------------- | -------------------------------------------------- |
| Sessions received    | Number of sessions recorded for this release       |
| Crashes received     | Number of crashes attributed to this release       |
| Unhandled error rate | Percentage of sessions that had an unhandled error |
| Release stage        | Which environment this release was deployed to     |

## Common metric combinations

* **Errors + Releases** — join these two entities to see which app versions introduced or resolved specific errors. Use Coupler.io's **Join** transformation to match on app version.
* **Events + Event fields** — combine raw events with custom metadata to filter by your own business-specific attributes (e.g., subscription tier, feature flag).
* **Errors (multiple projects)** — use **Append** to stack error data from multiple Bugsnag projects into a single table for cross-project stability reporting.
* **Pivots** — use pivot data to build aggregated views by OS, browser, or app version without processing raw events yourself.

## Use cases by role

{% tabs %}
{% tab title="Engineering" %}

* Monitor error rates by release to catch regressions immediately after deploys
* Join Errors and Releases to correlate crash spikes with specific app versions
* Export Events to BigQuery for long-term retention and custom SQL analysis
* Use Pivots to break down error frequency by OS or browser without manual grouping
  {% endtab %}

{% tab title="Product & QA" %}

* Track unhandled error rates across releases to measure stability improvements
* Export Errors to Google Sheets for sprint retrospectives and bug triage prioritization
* Monitor which user segments are most affected by using Event-level user dimensions
* Use Saved searches usage summaries to see which error queries your team relies on most
  {% endtab %}

{% tab title="Engineering Managers" %}

* Build Looker Studio dashboards showing error trends and resolution velocity over time
* Export Collaborators and Teams to audit project access and team assignments
* Send weekly error summaries to ChatGPT or Gemini for AI-generated stability reports
* Append data from multiple projects to compare stability across your product portfolio
  {% endtab %}
  {% endtabs %}

## Platform-specific notes

* The **Events** entity can return large volumes of data — set a narrow start date if you're pulling from a high-traffic project
* **Pivots** require a project context and return pre-aggregated data; they are not raw event records
* **Saved searches** and their usage summaries are project-scoped — you'll need to run separate data flows per project if you have many
* API access and available entities may vary depending on your Bugsnag plan; Enterprise plans have broader API access
* The **Personal Auth Token** grants access to all organizations and projects your Bugsnag user can see — use a dedicated service account token for production data flows