Graph Database for Technology Asset Data Ingestion
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Solution Overview
Problem
Organizations face challenges in understanding and managing their evolving technology assets due to rapid technological changes, leading to increased business risks, high costs, and regulatory compliance issues, as existing solutions lack automation and reliable information sources.
Innovation Solution
A system and method utilizing a graph database to create a 'single source of truth' for technology assets, integrating with various data sources, applying machine learning, and leveraging decentralized ledger technology to provide comprehensive asset intelligence, enabling real-time analytics and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data storage and query methods are used for technology assets, then implementation is simpler, but the ability to understand and manage evolving technology assets deteriorates due to lack of automation and reliable information sources
Solution Approach 1:
The patent segments technology asset management into distinct functional modules: event processing circuitry for data ingestion, graph database for structured storage, machine learning components for analysis, and visualization interfaces for user interaction. This modular segmentation enables reliable asset tracking while managing system complexity through organized functional divisions.
Solution Approach 2:
The patent introduces a graph database as an intermediary layer between raw technology asset data and user queries. This intermediary structure standardizes asset relationships and enables reliable information retrieval without requiring complex query logic, thus improving reliability while maintaining manageable complexity.
2Reliability
If comprehensive technology asset tracking is implemented, then business risk identification improves, but system complexity and cost increase
Solution Approach 1:
The patent implements preliminary action by continuously ingesting and processing technology asset events in real-time, maintaining an up-to-date graph database of asset relationships before risks manifest. This proactive approach enables early risk identification without requiring complex reactive analysis systems.
Solution Approach 2:
The patent incorporates feedback mechanisms where machine learning models analyze asset data patterns, generate risk assessments, and feed insights back into the system for continuous improvement. This feedback loop enhances risk identification capability while automating the process to manage complexity.
3Productivity
If manual asset management processes are used, then system complexity is lower, but productivity and cost-effectiveness deteriorate
Solution Approach 1:
The patent implements self-service automation where the system automatically ingests asset events from multiple sources, processes data through the graph database, generates risk assessments, and provides visualizations without manual intervention. This automation dramatically improves productivity while the modular architecture keeps complexity manageable.
Solution Approach 2:
The patent replaces manual mechanical asset management processes with automated computational systems including event processing circuitry, graph database operations, and machine learning algorithms. This substitution eliminates manual labor bottlenecks and improves productivity while automating complexity into standardized computational tasks.
Data Source
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AI summary
A system, method and computer program for handling inbound events on a technology network may include ingesting an inbound event from a connector, interfacing with one of different technology systems on the technology network, extracting a data element or a technology asset from the inbound event, and searching a database storing a new or existing inventory of technology assets in the technology network with respect to the data element or the technology asset. When the technology asset is extracted, a relationship between the technology asset and a record in the database is created. When the data element is extracted, a match between the data element and a record in the database is determined. When the match equals or exceeds a first predetermined threshold, the record in the database is enriched. When the match is less than a second predetermined threshold, a new technology asset in the database is created.