To get started, browse to insert any combination of JSON and Excel files in your data mapping project. Then, drag and drop to connect corresponding fields. MapForce includes a comprehensive library of data filters and functions to process your source data before writing it to the JSON or Excel target.
MapForce supports any-to-many data mapping as well as chained mappings.
When you need to map JSON and Excel (.xslx) data but don't have a schema corresponding to a JSON or JSON5 instance, MapForce will infer one for fast mapping according to the document structure.
When you select an Excel file for conversion, MapForce creates a graphical representation of the file structure, including rows, columns, and cells, as well as references to numbers and names. This component includes clickable icons which allow you to define and specify mappable data.
The Excel to JSON converter supports Excel versions 2007 and higher (OOXML). It allows you to select and map individual cells or ranges from each unique data table in the spreadsheet, and to address ranges statically or dynamically, avoiding manual extraction, export, or other pre-processing of complex Excel worksheets outside MapForce before they are inserted into your mapping design.
Once your JSON / Excel mapping is defined, MapForce automatically converts the data, which you can view on the Output tab. Converting JSON to Excel produces an Excel spreadsheet file (.xslx), and converting Excel to JSON produces a JSON instance document.
For advanced troubleshooting, MapForce includes an interactive data mapping debugger for tracing how data flows through source and target nodes during mapping execution.
To automate recurrent JSON to Excel conversion projects, you can deploy your MapForce projects to MapForce Server. MapForce Server provides high-performance automation of any-to-any data mapping projects at a fraction of the cost of legacy and big-iron data management products.