> ## Knowledge Base Index
> Fetch the complete knowledge base index at: https://help.datachamp.io/sitemap.xml
> Use this file to discover available pages before exploring further.
> Pure-Markdown content can be obtained by appending a '.md' suffix to the content URLs listed in the sitemap (without the trailing slash).

# Post Filters in Datachamp: What They Are and What Makes Them Different

#### ${color}[#1a63ba](Post Filters)

Post Filters are applied after the data has already been loaded into the report. Post Filters are especially useful when working with custom columns, calculated fields, or conditions that cannot be applied at the data source level. They support conditions such as `is empty`, `is not empty`, `contains`, `<`, `>` and `=`. 

**Example Post Filters:**
* Bundle SKU is not empty
 → Shows only bundle orders
![](https://storage.crisp.chat/users/helpdesk/website/-/d/0/0/f/d00f55635133d800/post-bundle_3ewpp.png)
| Please take a look at our article and YouTube video on how to export bundle orders in Datachamp – here we also used a post filter: 
| [How to Export Bundels](/en/article/how-to-export-bundels-15hstkw/)

* Product Title contains “Bundle”
 → Filters orders that include bundle products

![](https://storage.crisp.chat/users/helpdesk/website/-/d/0/0/f/d00f55635133d800/post-name_icctk1.png)
||| If your plan is limited to e.g. 1000 items, but you apply a post-filter to a dataset containing more items (e.g., 5000), the export will not be possible. This is because the system must first process all 5000 items in order to apply the post-filter. That total processing volume exceeds the 1000-item limit of your plan. 
||| Therefore, it is recommended to restrict the data volume at the source level whenever possible — e.g. filter by date, status, or other criteria — so that fewer than 1000 items are loaded in the first place. If your workflow requires scanning a large database, you will need a higher pricing plan to support the required processing volume.


#### ${color}[#1a63ba](Regular Filters)

These Filters are applied before the data is loaded into the report. They limit the data directly at the source, meaning that only matching records are retrieved from Shopify. This helps reduce the overall data volume and improves report performance.


**Example Filters:**
* Created at after 01/01/2026
 → Loads only orders created after this date
![](https://storage.crisp.chat/users/helpdesk/website/-/d/0/0/f/d00f55635133d800/pre-order-date_vxxcbo.png)

* Fulfillment Status = fulfilled
 → Loads only fulfilled orders
![](https://storage.crisp.chat/users/helpdesk/website/-/d/0/0/f/d00f55635133d800/pre-fullfillabe_18vhwo8.png)