What is better than an expert data wrangler? The answer is many expert wranglers. Collaborative Suggestions in Trifacta allow users to take advantage of the “collective data preparation intelligence” of your organization by suggesting transformations that you or other users in your organization have performed on similar types of data.
When enabled, Collaborative Suggestions add extra suggestion choices that present users with transformations that they or users in their organization have used before on similar columns. Enabling this feature can help speed up wrangling efficiency and improve knowledge sharing. As you continue to use Trifacta, the product’s suggestions will keep improving to suit your usage.
How to Enable
Collaborative Suggestions must be enabled by the workspace administrator in the Workspace Settings, and supports 3 levels of scope:
Disabled - Feature is completely off
Personal - Users will only see suggestions based off of previous transforms that they themselves have added in the past
Workspace - Users will see suggestions based off of previous transforms that they have added in the past as well as suggestions based off of transforms that other users in their workspace have added
By default, Collaborative Suggestions are enabled and set to the Workspace level.
Please contact your workspace administrator if you do not see these features in your workspace.
Note: Individual users can still choose to opt out of sharing their suggestions in their User Preferences. By unchecking “Share usage data to improve product intelligence”, their transforms will not be shared with the workspace. Their personal suggestions will still remain.
How to Use
When Collaborative Suggestions are enabled, additional transformations are automatically added to suggestion panels based on usage.
Personal suggestions are shown in a “Recently Used” section above all other suggestions.
Suggestions from the workspace show up as any other suggestion when selecting a column or brushing over similar data.
Note that in certain cases, suggestions may contain references to data values originating from other datasets that may not be highly relevant.
Tip: Collaborative Suggestions will improve over time. Based on how users interact with the transformations, the suggestions will get smarter.