*Insights
Filter, aggregate, and visualize your data in the Polyteia Platform.
The Insights feature empowers users to conduct in-depth data analysis within datasets. It facilitates the processing of large data volumes through functionalities such as selecting relevant columns, filtering, aggregating, and combining multiple datasets. Users can save and export the insights they create for further use.
Two ways to work with your data
Think of insights like having two different tools in your toolbox:
Visual Builder: Like using a simple calculator - just click the buttons you want. Pick your data, add filters, and create charts without typing anything.
SQL Editor: For advanced users who know SQL - write custom database queries to get exactly the data you need.
Features
Pick your columns: Choose which information you want to look at.
Add filters: Show only the data you care about, like "only show sales from 2023."
Summarize your data: Add up totals, count items, or find averages.
Make pivot tables: Organize your data like a fancy spreadsheet that does the math for you.
Sort and limit: Put your data in order and choose how many rows to show.
Join datasets: Combine information from different sources, like matching customer names with their orders.
Write SQL queries: For advanced users - write custom database queries for complex analysis.
Create charts and maps: Turn your numbers into pictures that are easy to understand.
Save your work: Keep your insights so you can come back to them later.
Export your results: Download your data to use in other programs like Excel.
Accessing insights
You can access and create insights in various ways, depending on what you want to do.
There are two ways to create a new insight:
From a dataset
Go to Home → Workspace → Solution → Datasets
Click on Explore dataset
Click on Create insight in the data view in the top right corner → The selected dataset will already be pre-filled in the insight editor.
From the insights list
Go to Home → Workspace → Solution → Insights
Click on Create new insight
Select the dataset you want to use in the insight builder
Roles and permissions
Insights have only one explicit role:
Insight Owner: The creator of an insight automatically becomes the Insight Owner, with exclusive rights to edit, rename, and delete the insight.
Permissions to create and execute insights are inherited from the dataset(s), meaning only dataset owners and editors can perform these actions. Dataset viewers can only see metadata of the dataset and insights, but cannot view, execute or modify insights.
Ownership cannot be transferred, but users can duplicate an insight to create a new version under their control.
Explicit permissions
The Insight Owner has limited administrative permissions for the insight, specifically for renaming and deletion. However, for all other actions – such as creating and executing the insight – the owner must also have the necessary permissions for the underlying dataset(s).
The creator of the insight automatically becomes the Insight Owner, and ownership cannot be transferred. If another user needs control over the insight, they can duplicate it to create a new version under their ownership.
Can edit the title and description of an insight.
✓
Can delete an insight.
✓
Inherited permissions from dataset(s)
Permissions for insights are inherited from the dataset(s) they are based on. This means that dataset owners and editors can create, edit, and execute insights, while dataset viewers have limited or no access.
Certain administrative actions – such as changing insight settings – are only available to the Insight Owner (the creator of the insight). Ownership cannot be transferred, but duplicating an insight allows other users to create their own versions with full control.
Can create an insight based on dataset(s).
✓
✓
✕
Can edit settings of an insight such as filters, aggregation, visualization. ⚠ Note: Insight Owner role required
✓
✓
✕
Can see the results and visualization of an insight.
✓
✓
✕
Can duplicate an insight.
✓
✓
✕
Can view title, description, and settings of an insight (e.g., filters, aggregation, etc.).
✓
✓
✓
Examples
Creating the insight
Lisa has Editor permissions for the dataset, enabling her to create insights based on it.
She sets up filters, aggregates the data, and generates a visualization.
Success: Dataset editors and owners inherit the permission to create insights.
Viewing the results
Lisa shares the link to the insight with her colleague Mark, a Dataset Viewer.
Mark cannot see the results of the insight because he only has access to the dataset's metadata, not the actual data.
Error: Mark needs at least Editor access to the dataset to view the insight results.
Solution: The dataset administrator should upgrade Mark's permissions to Editor, or Lisa needs to export the results and distribute them separately.
Editing the insight
Lisa makes a mistake in her aggregation and asks her teammate Emma to fix it.
Emma cannot edit the insight, even though she is also a dataset editor.
Error: Lisa is the Insight Owner, which means only she can edit, rename, or delete the insight.
Solution: Lisa can either make the changes herself or ask Emma to duplicate the insight and work on the copied version.
Sharing the insight for further analysis
Lisa's team wants to build upon the insight, but insights cannot be used as direct data sources for other insights.
Error: Insights are not shareable for further analysis.
Solution: Lisa must save the results in a dataset so others can use them for additional insights.
Best practices
Insight ownership cannot be transferred, so if someone else needs control, they must duplicate the insight. Use clear naming conventions to indicate ownership and purpose.
To see insight results, you must be a Dataset Owner or Editor — viewers cannot access results or visualizations.
Insights are not automatically saved—make sure to save regularly to avoid losing changes or analysis progress.
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