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As enterprise supply chains and consumer demand chains have beome globalized, they continue to inefficiently share information “one-up/one-down”. Profound "bullwhip effects" in the chains cause managers to scramble with inventory shortages and consumers attempting to understand product recalls, especially food safety recalls. Add to this the increasing usage of personal mobile devices by managers and consumers seeking real-time information about products, materials and ingredient sources. The popularity of mobile devices with consumers is inexorably tugging at enterprise IT departments to shifting to apps and services. But both consumer and enterprise data is a proprietary asset that must be selectively shared to be efficiently shared.

About Steve Holcombe

Unless otherwise noted, all content on this company blog site is authored by Steve Holcombe as President & CEO of Pardalis, Inc. More profile information: View Steve Holcombe's profile on LinkedIn

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Monday
Aug042008

The challenges in automated data transfer and data translation

The following quoted text (beginning at the bullet) is taken from the statement of prior art in US Patent 5,608,874 entitled System and method for automatic data file format translation and transmission having advanced features and filed in 1995.

  • "Computerized data, or electronically stored information, must frequently be moved from one computer to another. In the case of accounting data, for example, banks generally keep computerized records of all of transactions affecting their client's accounts--information which the clients often also wish to keep track of on their own computerized accounting systems. In response to this, a variety of sophisticated computer accounting programs have recently become available to users of small and medium powered computers. However, due to a variety of reasons discussed below, such clients usually have to re-enter data manually from paper printouts obtained from the data provider, for example, from statements from a bank. Manual re-entry of data is not only time-consuming, and hence expensive to undertake in terms of man-hours, but it also is likely to introduce errors into the data set. It has been estimated that manual data re-entry, verification, and validation costs several dollars per transaction.

    Methods of automated data transfer are known in the art. The "Intellicharge" system for Quicken (Intuit Inc., Menlo Park, Calif.) downloads credit card transaction information to a Quicken user's computer. The data used, however, comes from a uniform source--a single bank. Hence, Intellicharge does not employ a multiple-format data translation scheme, nor a multiple-source data transmission scheme. Similarly, in the United States Internal Revenue Service "Electronic Filing" program, data is entered and transmitted in a single, specific pre-prescribed format, to a single recipient.

    Methods of data translation are also known in the art. A software application entitled "Data Junction" (Tools and Techniques, Inc., Austin, Tex.) translates multiple formats of data. However, the package depends on manual operation to designate the files to be translated, and the formats of the source and destination files. Furthermore, this software does not perform any data transfer, verification, validation, exception reporting, or journal entry correction.

    Conventional electronic data exchange (EDI) systems involve two or more companies that have agreed to interact with one another according to a pre-designated standard dictated by the industry in which the transaction is taking place. In order for such a system to work for a given industry, there must be an agreed-upon standard that is used-much like in the case of the IRS system described above. Those industries that do not have such a standard cannot participate. Data analysis, such as exception reporting or statistical analysis, are not features of such systems. Obviously, such systems lack flexibility and versatility. Additionally, the computer systems that support conventional EDI are expensive to operate and maintain because they are specialized to serve specific industry segments, and hence cannot achieve the efficiency and low cost that economies of scale might permit in a more widely applicable system.

    In summary, conventional methods of automated data transfer, and of data translation, are quite limited, due primarily to limited network transfer capabilities, and the lack of universal data format standards. Hence, anyone wishing to automatically transfer data from a variety of computer systems to a variety of others must contend with a plethora of incompatible formats, and a lack of reliable transfer and error detection means. For these reasons, existing data transfer systems have been tailored to work with only one, or very few types of data sources and recipients, and these data translation methods rely heavily on manual intervention. Data transfer technologies and data translation technologies have not, in the prior art, been efficiently integrated."
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