Technical Language Processor for IT Data Encoding
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Solution Overview
Problem
Current systems face challenges in processing, storing, and analyzing vast amounts of data associated with information technology operational activities, struggling to evaluate interdependencies and technical language processing effectively, leading to inefficiencies in data storage and retrieval.
Innovation Solution
A computerized system that performs operational data processing, technical language processing, categorical data encoding, and dynamic data decoding to evaluate interdependencies, transform descriptive data into categorical records, and reduce storage requirements, while enabling efficient retrieval and evaluation of technology stability and change incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing systems are used to process and store data associated with information technology operational activities, then data processing capability is maintained at current levels, but memory requirements and processing time become excessively large and inefficient
Solution Approach 1:
The patent applies parameter changes by transforming the data representation format from descriptive text to categorical encoded values. This changes the fundamental parameters of data storage (from text strings to compact codes), dramatically reducing memory requirements while enabling more efficient processing and analysis of IT operational data.
Solution Approach 2:
The patent implements local quality by applying different processing treatments to different portions of the data. Descriptive fields are transformed into categorical codes while other fields maintain their original format. This selective transformation optimizes storage efficiency for specific data elements without compromising the integrity of the entire dataset.
2Loss of time
If existing systems are used to store records of information technology operational activities, then data retention is maintained, but retrieval time and processing overhead increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-processing and encoding data into categorical forms during data entry or initial storage. This advance preparation transforms descriptive data into compact, structured codes before retrieval is needed, eliminating the need for complex text analysis during query operations and significantly reducing retrieval time.
Solution Approach 2:
The patent implements segmentation by dividing records into distinct categorical fields (e.g., incident type, severity, status, technology component). This structured segmentation allows for efficient indexing and querying of specific attributes without processing entire text records, reducing retrieval time while managing complexity through organized data architecture.
3Reliability
If descriptive data is stored without transformation, then data integrity is preserved, but interdependency evaluation and technical language processing become ineffective
Solution Approach 1:
The patent introduces categorical codes as an intermediary representation between raw descriptive data and analysis processes. These codes serve as a mediating layer that preserves the essential meaning and relationships of the original data while enabling efficient computational processing, interdependency evaluation, and technical language analysis without requiring complex text processing algorithms.
Data Source
AI summary
Embodiments of the present invention relate to apparatuses, systems, methods and computer program products for a technology configuration system. Specifically, the system typically provides operational data processing of a plurality of records associated with information technology operational activities, for dynamic transformation of data and evaluation of interdependencies of technology resources. In other aspects, the system typically provides technical language processing of the plurality of records for transforming technical and descriptive data, and constructing categorical activity records. The system may be configured to achieve significant reduction in memory storage and processing requirements by performing categorical data encoding of the plurality of records. The system may employ a dynamic categorical data decoding process, which delivers a reduction in processing time when the encoded records are decoded for evaluating the exposure of technology change events to technology incidents and modifying such technology change events.