Unified Data Integration System for Enterprise Governance
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Solution Overview
Problem
Current data management systems lack a unified approach for effective data governance, leading to inefficiencies, inaccuracies, and scalability issues in integrating and curating enterprise data across multiple platforms, resulting in poor data veracity and increased resource duplication.
Innovation Solution
A data integration and curation system utilizing AI and ML for data cataloging, personalization, and governance, which creates a centralized data hub for validating data veracity and enabling smart data consumption by classifying and annotating data across various platforms, ensuring data quality and security through role-based access and anomaly detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple data platforms and repositories are used to cater to different data processing requirements, then data processing flexibility and specialization are improved, but data duplication and resource investment increase
Solution Approach 1:
The patent implements a unified data management approach that merges multiple data platforms into a single integrated system. The system consolidates data from disparate sources while maintaining the ability to process different data types and requirements, thereby eliminating data duplication while preserving processing flexibility.
Solution Approach 2:
The data management system is designed with multi-functional capabilities to handle various data processing requirements within a single platform. It provides universal data processing, storage, and retrieval functions that can accommodate different operational needs without requiring separate specialized systems.
2Ease of operation
If each operation and unit maintains its own data tools for discovery, curation, cataloging, governance, and sharing, then operational autonomy and specialization are improved, but system complexity and integration difficulty increase
Solution Approach 1:
The system segments data management functions into modular components that can be independently accessed and configured by different operations and units. Each user or department can customize their data discovery, curation, and governance tools according to their specific needs while the system maintains overall integration and coordination.
Solution Approach 2:
The patent introduces a centralized data management platform that acts as an intermediary between different operations and units. This mediator coordinates data access, governance, and sharing across the organization, reducing integration complexity while preserving operational autonomy through standardized interfaces and protocols.
3Adaptability or versatility
If data is spread across disparate sources and each source maintains its own data, then data source independence and local optimization are improved, but data veracity and unified governance deteriorate
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor and validate data quality across all data sources. Data veracity is maintained through automated quality checks, consistency validation, and feedback loops that ensure data accuracy while preserving the independence of individual data sources.
Solution Approach 2:
The patent combines data from multiple independent sources into a unified data structure that maintains data veracity. The system integrates data while implementing validation rules and governance protocols that ensure consistency and accuracy across all incorporated data sources.
4Adaptability or versatility
If different operations and units process and sanitize the same data differently, then operational customization and specific requirements fulfillment are improved, but data consistency and governance uniformity worsen
Solution Approach 1:
The system allows different operations and units to apply customized data processing and sanitization methods according to their specific requirements. Each department can configure local data quality rules and processing parameters while the system maintains overall data consistency through a unified governance framework.
Solution Approach 2:
The data processing system is designed to be dynamic and adaptable, allowing processing methods to change based on operational needs while maintaining data consistency. The system can adjust data sanitization and processing parameters dynamically while ensuring that final data outputs meet unified governance standards.
Data Source
AI summary
Examples of a data integration and curation system are provided. The system may receive data extracting requirement related to a digital initiative and obtain digital initiative data associated with the same. The system may classify the digital initiative data into various data domains and extract metadata therefrom based on data analysis. The system may determine a word index including a plurality of words from a knowledge database. The plurality of words may be mapped with the data domains to identify a data anomaly in the digital initiative data. The system may determine an anomaly correction for resolving the data anomaly and update the plurality of data domains to include the anomaly correction. The system may identify a user parameter associated with the digital initiative. The system may associate the user parameter with the metadata to create user parameter data associated with the user parameter to generate a data extraction result.