Data processing method and system thereof

Abstract

The invention opens a data-processing method and system, applys in the return process flow of product inquiry demand, the system includes: database, the original orders with data storage of products and recorded data corresponding with the original orders; Extracting module, based on the product demand inquiry the extracted data should be the first field data, and, accordingly obtain the corresponding field data of second data; and query processing module, according to the field data of second data for matching inquiry procedure in the database, should be made to the original orders data corresponding with field data of the second data, and from that original orders data extract the relevant data of the corresponding product demand inquiry, thus generate the corresponding answer recorded data, and revert the answer recorded data back to clients. This invention simplifies the procedure to save inquiries time, relatively increases efficiency of data-processing while reducing human error and improving inquiries correctness.

Description

technical field [0001] The present invention relates to a data processing method and system, in particular to a data processing method and system applied in product inquiry demand reply operations. Background technique [0002] In existing business activities, the communication between manufacturers and customers is becoming more and more frequent. Manufacturers often receive inquiries from customers in various forms, such as monthly product demand and material shortage information, and inquire about information such as shipment dates, invoice numbers, and material status of each batch of products. After receiving the inquiries, manufacturers , the logistics specialist is required to inquire and reply accordingly, fill in the shipping date and invoice number of different batches of products under each customer order number, and reply the result to the customer. In the existing operation process: first, according to the customer order number in the inquiry of monthly product...

AI Technical Summary

Problems solved by technology

[0003] There is a certain deficiency in the above-mentioned prior art. The deficiency lies in that there are often many batches of products that need to be queried under the same group of customer order numbers that are inquired about monthly product demand and material shortage information. Therefore, in the customer’s original order data There are many batches of products that need to be used under a manufacturer’s internal order number. If the query process is all done manually, it usually takes one working day to complete a monthly product demand or material shortage information query. ; Moreover, not every batch of products will be queried. It often happens that the SAP system query cannot be matched. At this time, it is necessary to query the original order from the customer's original order data to obtain the matching order record and reply to the customer. Therefore, Due to the large amount of order data and the messy distribution of order records, and the operation mode of manual query is very inconvenient, a lot of working time and human resources are wasted; moreover, engineers and technicians manually process and analyze so many and messy data for a long time , it is prone to visual fatigue and mental fatigue, which may cause human errors such as data omission, overwriting, and wrong writing, which will cause incorrect data in reply to customers, affect the communication between manufacturers and customers, and even cause Customer churn due to customer distrust of vendors

[0004] Therefore, how to propose a data processing method and system to avoid various deficiencies in the prior art, so as to save working time and improve the efficiency of query operations, and also avoid data omissions, overwrites, etc. caused by all manual operations. Miswriting and other human errors occur, which is actually a technical problem that needs to be solved urgently

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