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

# Filters, sorts, and grouping

> Use database controls to review the right slice of records without changing the underlying data.

Filters, sorting, and grouping help you turn a large database into something you can actually review. They do not change the source records. They change how you inspect the dataset.

![Placeholder image for future Oculon screenshot showing database filters, sorting controls, and grouped records](https://mintcdn.com/oculon/86VwbwjFLcFRyaEK/images/databases/filters-sorts-grouping-placeholder.svg?fit=max\&auto=format\&n=86VwbwjFLcFRyaEK\&q=85\&s=73e8ec58530a8527521d39b70aff2630)

## Why these controls matter

A database becomes more useful when you can answer practical questions quickly, such as:

* which records belong to one region or owner
* which items are newest or highest value
* which categories contain the most records
* which rows need cleanup before the data feeds a model

These controls make that review possible without changing the structure.

## Use filters to narrow the record set

Filters help you review only the rows that matter to the current question.

Common examples include:

* one business unit
* one status
* one date window
* records missing a required field

Filters are especially useful when you are checking data quality before the records flow into a model.

## Use sorting to surface priority

Sorting makes the database easier to scan.

You might sort by:

* newest first
* largest values first
* alphabetical category order
* records most likely to need cleanup

Use a sort order that matches the review goal. A useful sort should help the next decision happen faster.

## Use grouping to review structure

Grouping is useful when the same dataset needs to be reviewed by category, owner, status, or another shared field.

This helps when you want to:

* compare the size of different groups
* check whether categories are used consistently
* spot missing mappings or outliers
* confirm that the structure will make sense in downstream reporting

## Review time-aware data carefully

If the database contains time fields, always confirm which time slice you are reviewing before you assume the records are wrong.

A time-aware dataset can look inconsistent when the filter or grouping does not match the intended period.

## Keep review logic readable

Too many hidden filters or layers of grouping can make a database hard to trust.

If people need several hidden rules to understand the table, the structure may need cleanup or the review should move into a more purpose-built view.

## Related pages

* [Working with data](https://oculon.mintlify.site/docs-new/databases/working-with-data.md)
* [Database structure](https://oculon.mintlify.site/docs-new/databases/database-structure.md)
* [Data mismatches](https://oculon.mintlify.site/docs-new/troubleshooting/data-mismatches.md)
* [Views: Filters, sorts, and grouping](https://oculon.mintlify.site/docs-new/views/filters-sorts-and-grouping.md)


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