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# Fix Mammoth errors after a source's columns change

> Fix Mammoth pipeline errors and failed data additions after a source column is renamed, removed or retyped, including Send to Dataset column mapping errors.

When a column is renamed, removed or retyped at the source, two things can break: pipeline tasks that use the column, and data additions that no longer match the dataset's columns. A failed data pull shows in the notifications bell with the dataset's name. See [Notifications](https://mammoth.io/docs/learn/automate/notifications/).

## Fix pipeline errors after a source change

See [Fix a failing step](https://mammoth.io/docs/learn/clean-and-shape/fix-a-failing-step/) for each fix.

| Error | Cause | Fix |
| --- | --- | --- |
| Column missing | A task uses a column that was renamed, removed or retyped at the source | Find the task that uses it, point it at the correct column, and re-run the pipeline |
| Type change | A column's data type changed at the source, so tasks that depend on the type fail | Update the affected tasks, or add a type conversion step earlier in the pipeline |
| Dependency error | A task depends on another task or a secondary dataset that is in error. Tasks don't run if their dependencies failed | Resolve the upstream error first, then re-run the pipeline |

A slow run isn't an error: the pipeline still completes. It usually means the source grew a lot, or a task processes more rows than you expected. Find the slow task and add filters to cut the rows it handles. See [Speed up pipelines and connectors](https://mammoth.io/docs/learn/help/performance/).

## Fix data that doesn't match the dataset's columns

When you add data to a dataset (through a Dataset Refresh, a Data Consolidation or a manual addition), Mammoth compares the incoming data with the existing columns. A missing, renamed or retyped column is handled by the dataset's **If column type doesn't match** and column mapping settings: Mammoth can convert the column to text, convert incompatible values to null, or leave the dataset unchanged. See [Add or replace data](https://mammoth.io/docs/learn/get-data-in/add-or-replace-data/).

To fix a failed addition, make the incoming data match the dataset's columns at the source, or adjust the dataset's mapping settings. Then retry.

### Fix Send to Dataset column errors

**Send to Dataset** sends processed data from one View to a destination dataset. If a mapped column no longer exists in the source View or the destination dataset, the send fails.

1. Open the Send to Dataset configuration.
2. Confirm every mapped column exists in both the source View and the destination dataset.
3. Update the mapping and retry.

## Related

- [Fix connection and refresh failures](https://mammoth.io/docs/learn/help/connection-failures/): expired keys, firewalls and rate limits.
- [Fix a failing step](https://mammoth.io/docs/learn/clean-and-shape/fix-a-failing-step/): fix any red pipeline task.
- [Error messages](https://mammoth.io/docs/learn/help/errors/): the exact messages for schema errors.

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Source: https://mammoth.io/docs/learn/help/source-changes.md · Updated: 2026-11-08