# Examples & Use Cases

Source: https://userguide.qualytics.io/cli/examples/

End-to-end scenarios that show the Qualytics CLI in action: real customer workflows, basic to advanced. Pick the scenario that matches what you're trying to do; each one is a self-contained guide with the full CLI sequence, the API endpoints called behind the scenes, a Python equivalent, the minimum permissions required, and troubleshooting for the most common failures.

> **Info: How each page is structured**
>
> Every example below follows the same shape: **Goal → Permissions → Prerequisites → CLI workflow → Behind the scenes → Python equivalent → Variations → Troubleshooting → Related**. Skim the section that matters most for your situation; the rest is there when you need it.

## Datastores

Onboard new sources, one at a time or in bulk.

| Scenario | What it covers |
| --- | --- |
| [Onboard a single datastore](https://userguide.qualytics.io/cli/examples/onboard-single-datastore/) | Connection → datastore → sync → profile → scan, plus DFS and IAM-role variations. |
| [Bulk datastore onboarding](https://userguide.qualytics.io/cli/examples/bulk-datastore-onboarding/) | Define many datastores in YAML, apply the whole folder with `config import`. |

## Operations

Run the recurring data quality pipeline.

| Scenario | What it covers |
| --- | --- |
| [Daily sync, profile, and scan](https://userguide.qualytics.io/cli/examples/daily-pipeline/) | The standard three-step pipeline, foreground and background, single and multi-datastore. |
| [Targeted scans](https://userguide.qualytics.io/cli/examples/targeted-scans/) | Scan only specific containers or tag-filtered subsets. |
| [Incremental scans for large tables](https://userguide.qualytics.io/cli/examples/incremental-scans/) | `--incremental` with `--greater-than-time` or `--greater-than-batch` for billion-row tables. |

## Quality Checks

Author, promote, and govern checks.

| Scenario | What it covers |
| --- | --- |
| [Bulk-create quality checks](https://userguide.qualytics.io/cli/examples/bulk-create-quality-checks/) | Create many checks in one shot from a YAML library. |
| [Promote checks Dev to Prod](https://userguide.qualytics.io/cli/examples/promote-checks-dev-prod/) | Export, version in Git, import to Prod with idempotent upsert. |
| [Audit and clean up draft checks](https://userguide.qualytics.io/cli/examples/audit-draft-checks/) | Review the queue of `Draft` checks, promote keepers, archive the rest. |
| [Manage check templates](https://userguide.qualytics.io/cli/examples/manage-check-templates/) | Export, import, and govern reusable check templates. |

## Anomalies

Triage at scale.

| Scenario | What it covers |
| --- | --- |
| [Bulk anomaly triage](https://userguide.qualytics.io/cli/examples/bulk-anomaly-triage/) | Filter, bulk update with assignees, bulk archive with the right outcome status. |
| [Daily triage automation](https://userguide.qualytics.io/cli/examples/triage-automation/) | Cron-driven script that auto-archives stale anomalies and routes fresh ones to on-call. |

## Computed Containers

SQL-defined virtual tables and joins.

| Scenario | What it covers |
| --- | --- |
| [Bulk import computed tables from CSV](https://userguide.qualytics.io/cli/examples/bulk-import-computed-tables/) | Drop a CSV of name/description/query rows; the CLI registers them all and creates checks per row. |
| [Build a computed join](https://userguide.qualytics.io/cli/examples/build-computed-join/) | Combine two existing containers into a new joined view without writing the SQL by hand. |

## Configuration as Code

Treat the whole Qualytics config as version-controlled YAML.

| Scenario | What it covers |
| --- | --- |
| [Export and import full configuration](https://userguide.qualytics.io/cli/examples/export-import-config/) | Connections, datastores, containers, fields, and checks exported as a Git-friendly folder, importable into any environment. |
| [Drift detection between environments](https://userguide.qualytics.io/cli/examples/drift-detection/) | Detect when the live config has been changed in the UI without going through Git. |

## Automation

Schedule recurring work and integrate with CI.

| Scenario | What it covers |
| --- | --- |
| [Scheduled metadata exports](https://userguide.qualytics.io/cli/examples/scheduled-metadata-exports/) | Daily/hourly snapshots of anomalies, checks, and field profiles to your enrichment destination. |
| [GitHub Actions pipelines](https://userguide.qualytics.io/cli/examples/github-actions-pipelines/) | PR validation, tagged-release promotion to Prod, nightly scans, drift checks. |

## AI Integration

Let Claude Code, Cursor, and other AI assistants use Qualytics directly.

| Scenario | What it covers |
| --- | --- |
| [Connect MCP clients](https://userguide.qualytics.io/cli/examples/connect-mcp-clients/) | Use the `qualytics mcp serve` bridge when an assistant should reuse your CLI login. |

---

## Permission and role primer

Most CLI commands check **two** kinds of permissions before they do anything. Each example page lists the minimums for the endpoints it calls.

| Layer | What it controls | Levels |
| --- | --- | --- |
| **User role** (global) | What kinds of resources you can touch at all | `Admin` > `Manager` > `Member` |
| **Team permission** (per resource) | What you can do with a specific resource based on your team membership | `Editor` > `Author` > `Drafter` > `Viewer` > `Reporter` |

If you're not sure what role your token has, run:

```bash
qualytics auth status
```

For the full conceptual model see [Team Permissions](https://userguide.qualytics.io/settings/access/teams/team-permissions/overview/).

*Last updated: September 29, 2026.*