The Dromo importer walks a user through the process of validating, cleaning, and transforming a data file, guaranteeing that the final output meets all your quality standards and is in the form you expect.
To configure Dromo, you simply define what the final data file should look like, along with any validation rules or constraints. You do this by creating a "schema" for each import, either in code (Dromo Pro only) or using the no-code Schema Studio.
To use Dromo, you or an end user must:
- Initiate an import. This happens in one of two ways:
- A user opens the embedded Dromo importer and uploads a file (or manually enters their data)
- You send a file to the Headless API (this feature is a premium add-on)
- Match columns. After uploading a file, the user matches their column names to the names you require (where possible, the importer does this automatically on their behalf or uses AI to recommend matches).
- Run bulk transformations. The user may perform bulk transformations on the data, with suggestions powered by AI.
- Clean remaining errors. The user may review the final data in a familiar workbook interface, which highlights and annotates any errors. They can quickly isolate and diagnose problems and correct the data.
- If a user prefers to fix errors offline, they may download the current state of the import as an Excel workbook, complete with error annotations, from the review screen. Whenever they re-upload that file, the importer will pick up where they left off.
Dromo outputs the final cleaned data as a JSON object. You can now move the file to the next stage of your data pipeline (e.g., upsert it into a database, attach it to an email, save it in cloud storage) with confidence.
Dromo also provides access to metadata about the import and has an option to view final data as a CSV file.