Preview of Transformed EDI Data

> For the complete documentation index, see [llms.txt](https://docs-fr.docbits.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs-fr.docbits.com/administration-and-setup/setup/document-types/edi-data-transformation-process.md). # Processus de Transformation des Données EDI ####

#### Step 1: Structure Descriptor * **Format**: JSON * **Purpose**: This step involves defining the structure of the EDI data. It includes specifying segments such as `SAC`, `N1`, and `PO1`, and details the fields contained within each segment. For segments that contain nested structures, loops are defined to properly organize the data hierarchy. ```json { "SAC": {"fields": ["SAC", "DTM", "TX1", "TD5"]}, "N1": {"fields": ["N1", "N2", "N3", "N4", "PER"]}, "PO1": { "fields": ["PO1", "REF"], "loops": { "SAC": {"fields": ["SAC", "TX1", "DTM"]} } } } ``` #### Step 2: Transformation Using XSLT * **Format**: XSLT * **Purpose**: This step involves transforming the structured JSON data into a structured XML format, specifically tailoring the output to meet the requirements for further processing or integration. This transformation helps in extracting precise information like acknowledgement types, order details, and conditional elements based on specific values. ```xml

With detail, no change With detail and change Unknown ``` #### Step 3: Preview (HTML Conversion) * **Format**: XSLT (outputting HTML) * **Purpose**: Converts the XML data from Step 2 into an HTML format for previewing the transformed data in a readable and visually appealing format. The HTML layout includes styles for presentation and structures data like purchase orders, supplier details, and order terms for easy viewing. ```xml Preview of Transformed EDI Data

``` #### Step 4: Extraction Paths * **Format**: JSON * **Purpose**: Specifies JSON paths for extracting key values from the XML data produced in Step 2. These paths are used to retrieve specific data points such as purchase orders and currency, which are crucial for downstream processing and integration into other systems. ```json { "fields": { "purchase_order": "//ORDER_CONFIRMATION/PURCHASE_ORDER/text()", "currency": "//ORDER_CONFIRMATION/CURRENCY/text()", ... }, "tables": [ { "name": "ORDER_CONFIRMATION_TABLE", "row_path": "//ORDER_CONFIRMATION/ORDER_LINES/ORDER_LINE", "columns": [ {"name": "POSITION", "path": "POSITION/text()"}, ... ] } ] } ``` This updated sequence ensures a thorough process, transforming raw EDI data into structured, actionable information using JSON for data structuring, XSLT for transformation and HTML preview, followed by JSON paths for data extraction and integration. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs-fr.docbits.com/administration-and-setup/setup/document-types/edi-data-transformation-process.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.