EDI Archives

Drive VDA EDI Conversion and Transformation with MapForce

May 3, 2023/in Data Integration, EDI /by Erin Cavanaugh

EDI (electronic data interchange) messages are used in a variety of industries for transmitting business information such as invoices, shipping notices, and purchase orders—which were traditionally recorded on paper—electronically. EDI transactions are structured according to standards that describe the format of each message. Adherence to a standard format enables the messages to be transmitted electronically between the computer systems of trading partners without human interaction.

Different industries take advantage of specialized EDI formats that are relevant to their business, and one such popular format is VDA EDI, which is used by the German automotive industry.

To work with VDA messages efficiently, companies often need to transform them to other formats, for instance, for storage in a backend database, or convert them to other EDI message formats for compatibility among systems. Altova MapForce makes this easy, with support for VDA as well as several other popular EDI standards. Let’s see how it works.

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Automatically Convert EDI to XML

May 18, 2022/in Data Integration, EDI, Tools /by David McGahey

Electronic Data Interchange (EDI) has proven to be a durable business-to-business communication technology in use today with history dating to the 1960s and even earlier. Efficient EDI data encoding reduced transaction payload size and improved data transfer speeds at a time when messages were sent over teletype at speeds equivalent to a 300 baud modem. EDI standards bodies promote wide acceptance among enterprises, and systematic evolution of new EDI formats extends support across industries. EDI improves profitability and is a dominant format for e-commerce data exchange.

Despite the advantages, EDI files are barely human readable and need to be translated and mapped for compatibility with other business technologies. Altova MapForce is a graphical EDI mapping tool with native support for all major business data formats in use today, including XML, JSON, databases, flat files, Excel, and Web services, as well as the EDIFACT, X12, HL7, NCPDP SCRIPT, IDoc, PADIS, and SWIFT EDI transaction sets. MapForce can even automatically convert EDI to XML without the need to specify a target XML Schema or perform any manual mapping.

Tags: data conversion, data mapping, EDI, XML

New tools for JSON, EDI, SWIFT, and XBRL in Version 2021

October 14, 2020/in Development, EDI, JSON, XBRL /by Erin Cavanaugh

As standards-based technologies and their applications evolve, so does the functionality that users require from developer tools. In our latest release, we’ve added new ways to work with XBRL, JSON, EDI, and more that help Altova customers work faster and more efficiently.

Let’s take a look at some highlights from the Altova Software Version 2021 release.

Tags: EDI, MapForce, new features, StyleVision, SWIFT, v2021, XBRL, XMLSpy

New Data Integration Tools

March 25, 2020/in Data Integration, Database, EDI /by Erin Cavanaugh

Altova MissionKit tools offer numerous ways to connect to, query, and integrate data from disparate sources. With multiple product releases each year, we’re constantly working to deliver increased power and efficiency for data integration, while adding features requested by customers. This includes ongoing updates to built-in support for all major SQL databases across the product line.

Let’s take a look at some of the recently added tools and enhancements.

New data integration tools in Altova's release

Faster EDI Data Translation

March 7, 2016/in Data Integration, EDI /by David McGahey

Electronic Data Interchange (EDI) standards accelerate commerce worldwide by allowing companies and other organizations – even those in different regions, using different languages and currencies – to send and receive unambiguous information. Some EDI communication protocols and message formats still in wide use today were developed over 30 years ago, when telecommunication systems were slower and data storage was more expensive.

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