Electronic data interchange (EDI) is one of the ways businesses use for exchanging computer-to-computer business information based on approved formatting standards and schemas. For example, millions of companies around the world transmit data associated with business transactions (e.g., purchase orders, shipping/air bills, invoices, or the like) using EDI to conduct commerce.
In a typical EDI transaction model, a large business entity or an EDI integration broker trades with numerous partners and has the technical capability to handle numerous EDI transaction data in various EDI formats and schemas. These large business entities, also known as “hubs,” transact with one or more suppliers, also known as “spokes”. Each of the spokes typically is a relatively small business entity that is only capable of dealing with one hub.
Frequently, EDI documents are exchanged in batches between the hub and the spokes, and each batch may include multiple types or a collection of business documents. For example, the batch of EDI documents from the hub to the spokes may include: purchase order, payment advice, return material notifications etc.
Trading parties also may modify the EDI formats, and consequently the schemas associated with the EDI documents, during their course of conducting business to serve their business and integration needs. After such modification, business entities frequently use an EDI transformation system to transform EDI data or EDI messages formatted from the previous schema to the modified schema.
In transforming EDI transaction data formatted according to previous or old EDI schemas, EDI transformation systems (e.g., systems using XSLT) typically perform a transformation of all EDI transaction data from the previous EDI schemas to the new EDI formats. As such, such systems load the EDI message, which includes a batched transaction data with a size of 30 to 40 MB, in a memory storage area for the transformation to take place. This transformation thus unnecessarily poses a limit on the size of documents that can be loaded without compromising performance significantly. In addition, for the spokes that lack advanced processing equipment to handle such transformation efficiently, existing transformation method places heavy burden on the transformation performance and resources of the spokes.