Segmenter: Working with Large Amounts of Data
Note: Coming Soon
The Segmenter is a helpful feature for users who work with large datasets inside Boost.space. When a module contains many records, loading the full dataset can take time. The Segmenter helps by allowing you to load and view only a part of the data at once.
When Segmenter is Active
The Segmenter can be:
- Turned on manually in the System Settings, or
- Automatically activated when a module contains more than 100,000 records.
When it’s active, the system loads only selected parts of your data instead of the whole module at once. This makes the interface faster and more responsive.
Creating a Segment
When you open a module, you will see a button at the top that says “+ Segment”.
You can create multiple segments, each with its own filter. Boost.space keeps the last 5 opened segments in the local cache. If you open a sixth one, the oldest one is removed from the cache.
When you add a New segment, a filter table appears. You can choose:
- Field – e.g. Product ID, Creator, etc.
- Operation – e.g. equals, greater than, starts with
- Value – the value to compare
This allows you to define exactly what records should be included in the segment.
Once saved, the segment appears in the top bar. Clicking it shows only the filtered records.
Segment Actions
Right-clicking on a segment opens a menu. One useful option here is Copy filter.
This copies the filter rules from the segment. You can then use this in other parts of Boost.space, like the Integrator.
Using Segment Filters in the Integrator
In the Integrator, when mapping fields or creating conditions, you can paste the copied filter. This helps you keep the same logic in both the module and your automation.
The Segmenter is a practical tool to handle large datasets without slowing down your workflow. By breaking data into smaller parts, you can focus on specific segments, load data faster, and reuse filters in your automation tasks. Using segments helps keep your workspace organized and responsive, making it easier to work with big data inside Boost.space.
If you need help with anything, please contact us at [email protected].