Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
2000-12-30
2003-10-21
Metjahic, Safet (Department: 2171)
Data processing: database and file management or data structures
Database design
Data structure types
Reexamination Certificate
active
06636864
ABSTRACT:
FIELD OF INVENTION
The present invention relates generally to methods and systems for data file creation. Embodiments of the present invention provide for automatic data extraction and data feed file creation at remote locations and transferring completed data feed files to locations electronically accessible to a software application.
BACKGROUND
The ability to gather and manipulate data is increasingly important in today's society. Small businesses and large corporations alike are aware that compiling, manipulating and reviewing data can provide valuable information about their present and future customers. Whether it is data on product usage or data on seasonal trends in customer purchases, the need to locate, gather on demand, and manipulate data is important. Even computer software designers are aware that the ability to manipulate and present data may provide valuable insight to business owners and managers. To that end, many software designers have developed software applications capable of manipulating and presenting data in a variety of ways to help improve data compilation and manipulation.
Companies have long recognized the need for gathering and storing data relating to its customers, suppliers etc. At one time, this data was kept in boxes and stored in rooms. When storage space for data became cumbersome, data was often transferred to mainframe computers and other like electronic data storage devices. These storage devices allow massive electronic data files to be stored in one location. However, when mainframes and other like devices became the preferred method of storing large volumes of data, the need and the technology to perform data manipulations to present data in a variety of ways was not as prevalent as it is today. Instead, the mainframe was often used to archive data that was important but infrequently accessed.
As times changed so did the purpose of storing data on a mainframe and the frequency with which this data was accessed. No longer is data stored on a mainframe primarily because it is historic information that needs to be archived. To the contrary, data is sometimes stored on a mainframe because it is so voluminous that it would occupy too much space on a local area network server, a wide area network server or a desktop computer hard drive. The increased frequency with which data on a mainframes is needed creates problems with efficiently providing desktop software applications access to the data when it is stored on a remote mainframe or other like data storage device.
To obtain information stored in data files on a mainframe, end-users often have to print the entire data file from the mainframe. Oftentimes, the data manipulation performed by the desktop software application does not require all the data stored in the data file on the mainframe. The end-user is, therefore, forced to manually filter through the voluminous data file, pinpoint the data needed and manually create a data feed file for use by the desktop software application. Thus, there is an obvious need for the capability to automatically and electronically select the data stored on the mainframe and generate a data feed file that is accessible to desktop software applications for data manipulation and presentation.
SUMMARY OF INVENTION
Generally speaking, the present invention relates to a method and system for generating a data file by extracting specified data from a larger raw data file. The goal of this invention is to generate a data feed file that can be used by desktop applications for any number of operations including, but not limited to, data compilation and data tracking.
According to an embodiment of this invention, the raw data file contains large volumes of related data. The raw data file is comprised of multiple records, each record comprised of at least one data field. Each data field contains the same category of data in each record of the raw data file. Assume, for this example and all examples hereafter, that the raw data file contains customer-billing information. Each record in the raw data file would therefore contain customer-billing information pertaining to an individual customer. Each record in the raw data file would further be comprised of data fields, each containing a different category of data, such as customer name, customer address, the customer phone number etc. Below is an example of the records and data fields of a raw data file.
In an embodiment of this invention, the raw data file is so voluminous that it is stored on a remote data storage device, such as a mainframe, instead of being stored on a computer hard drive, local area network (LAN) or other like electronic storage device accessible to a user-preferred desktop software application or applications.
In an embodiment of this invention, desktop software applications include, but are not limited to, the following commonly known software applications: MICROSOFT EXCEL, MICROSOFT ACCESS, and ORACLE. These software applications and other like applications, are used to perform operations such as, data compiling, data tracking and other types of data manipulation. In an embodiment of this invention, the user-preferred software application uses data contained in a raw data file that resides on a mainframe or other like data storage device. In an aspect of the invention, the operation performed by the desktop application, may not require all the data contained in the raw data file. Instead, the desired data manipulation may only require select data contained in the raw data file. It is the goal of this invention to generate a data feed file by extracting only needed data from the raw data file. The data feed file will then contain only the data the user-preferred desktop software application needs to perform its designated operation.
According to an embodiment of this invention, the data feed file is generated by extracting the desired data from the raw data file and populating the data feed file with the extracted data. To determine what data to include in the data feed file, the end-user develops a set of data feed file criteria.
In an embodiment of the invention, the data feed file criteria identifies the location of the desired data in the raw data file by identifying the data field in each record of the raw data file that contains the desired data. The data field containing the desired data may be identified in any number of ways. In another embodiment of the invention, the location of the data filed is identified by the category of data the data field contains. For example, a data field in each record of the raw data file may contain the amount payable by each customer. In such cases, the data field could be identified as the “amount payable data field”.
In another embodiment of the present invention, the location of the data field is identified by the position of the data field in relation to other data fields in each record of the raw data file. For example, the data field that contains the desired data may be the fifth data field from the left in each record of the raw data file. In such cases, the data field could be identified as data field number five (5).
In addition to identifying the location of the desired data in the raw data file, the data feed file criteria may specify additional requirements for data to be included in the data feed file. For example, the data feed file criteria may specify that data located in the amount payable data field should be included in the data feed file only if the amount payable is greater than two hundred dollars ($200).
In yet another embodiment of the invention, the set of data feed file criteria may further contain criteria for including data not in any data field of the raw data file. For example, different service fees may apply to customers depending on the customer's zip code. However, the raw data file may not contain the various fees. In such cases, the data feed file criteria may specify that a data field in the data feed file include a designated service fee for customers depending on the customer's zip code.
In an embod
Al-Hashemi Sana
BellSouth Intellectual Property Corporation
Cantor & Colburn LLP
Metjahic Safet
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