How does DataFlowMapper compare to traditional ETL tools?

Unlike complex ETL platforms that can be overwhelming and require coding knowledge, or basic mapping tools that lack flexibility, DataFlowMapper offers a perfect balance of power and simplicity through its visual interface and Custom Logic Builder.

What types of data transformations can I perform?

DataFlowMapper supports comprehensive data transformations through our visual interface, including:

• String operations (UPPER, LOWER, TRIM, REPLACE, CONCAT, etc.)
• Mathematical functions (SUM, MULTIPLY, DIVIDE, ROUND, etc.)
• Date formatting and manipulations
• Type conversions and data cleaning
• List operations
• Custom python snippets for power users and flexibility

How does the Custom Logic Builder work?

The Custom Logic Builder features an intuitive multi-tab interface that lets you:

• Define variables and create conditional logic using a visual IF/THEN builder
• Use AND/OR logic with support for multiple conditions and nesting (one level deep)
• Apply pre-built functions for common transformations
• Preview transformations in real-time
• Use the Manual tab to write Python snippets for advanced transformations

What file formats and sizes are supported?

DataFlowMapper supports CSV, Excel (xlsx, xls), and JSON formats with drag-and-drop file upload capabilities. The platform works optimally with files containing hundreds of thousands of rows, and all formats are fully supported for both input and output. We currently have a 200mb limit per file.

How does the visual mapping interface work?

Our visual interface lets you map fields through drag-and-drop actions. You can either create direct field-to-field mappings or use the Custom Logic Builder for complex transformations. The interface shows source fields, destination fields, and a real-time preview of your transformation logic. Each field can have either a direct mapping or custom logic, but not both. Within the Custom Logic Builder, users can input a row on Return Results tab to test what the transforation will return to help validate your mapping on the fly.

Can I save and reuse my data transformation mappings?

Yes! You can download your mappings as CSV files, which define your source fields, destination fields, and transformation logic. These mapping files can be saved locally and reused for future transformations. Simply upload your saved mapping file when you need to perform the same transformation again or if you'd like to edit it.

How does DataFlowMapper handle data security?

DataFlowMapper prioritizes data security by never storing your transformation data. All transformations are processed on our secure Railway server, and only basic user information is stored in our database. Your data is processed in memory and immediately discarded after the transformation is complete. Payments and authorization are handled by third-party services.