Data Conversion Method Using Segmentation and Key Value Library
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Solution Overview
Problem
The exponential growth of data in various industries, driven by regulatory compliance and the rise of 'big data,' poses challenges in efficient storage and transmission, necessitating effective data compression and encryption methods.
Innovation Solution
A data conversion method that identifies patterns in data files, assigns key values, builds a library of these values, replaces the data file with a key value file, and compresses or encrypts it, significantly reducing file size for faster transmission and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored and transmitted in its original form, then data integrity is maintained, but storage space is consumed and transmission time increases
Solution Approach 1:
The data file is divided into multiple segments or blocks, each of which is independently processed through the conversion process. This segmentation allows the system to handle large files efficiently by processing smaller units in parallel, reducing overall transmission time while maintaining data integrity through systematic reconstruction of the original file from converted segments.
Solution Approach 2:
The invention transforms data by changing its representation parameters - converting original data into a different format or encoding scheme that occupies less space. This parameter transformation reduces the quantity of data stored and transmitted while preserving the ability to reconstruct the original information when needed, directly addressing both storage space consumption and transmission time issues.
2Quantity of substance
If data compression is applied to reduce file size, then storage efficiency improves, but data security and recoverability may be compromised
Solution Approach 1:
The invention creates a converted copy of the original data that maintains all essential information while occupying less space. This copying approach ensures that the compressed representation is not a lossy approximation but rather an alternative encoding that can be fully reconstructed back to the original data, thereby maintaining both security and recoverability while achieving compression goals.
Data Source
AI summary
Methods of converting data are provided. In one embodiment, a data conversion method is provided that includes partitioning the data file into a plurality of file segments. The method also includes assigning a plurality of key values for each of the plurality of file segments. Also, the method includes forming a key value file from the plurality of key values.