Data Quality Management System for Datasheet Redundancy Control
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Solution Overview
Problem
As databases and datasheets in data centers grow rapidly, issues arise such as disordered storage of datasheets, redundancy, inconsistency, and unclear data flow, making it difficult to manage and control data quality effectively.
Innovation Solution
A method and apparatus for data quality management that involves receiving application information from service sub-systems, resolving datasheet operation trigger information to obtain flow information, querying history information to determine datasheet names and consistency, and instructing the data center to store or update datasheets accordingly, ensuring proper naming conventions and reducing redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple sub-systems store datasheets in a shared tablespace without centralized management, then data storage capacity increases, but datasheet searching becomes difficult and data quality deteriorates
Solution Approach 1:
The patent introduces a data center as an intermediary layer between multiple sub-systems and the shared tablespace. The data center implements centralized management mechanisms including automatic naming conventions, deduplication algorithms, and metadata indexing, which resolve the contradiction by enabling both large-scale storage and efficient retrieval through centralized coordination
2Adaptability or versatility
If datasheets are stored in multiple tablespaces across different sub-systems, then data accessibility improves, but redundancy increases and storage efficiency decreases
Solution Approach 1:
The patent implements a selective copying mechanism where the data center creates standardized copies of datasheets only when necessary for specific sub-systems, rather than allowing uncontrolled duplication. The system uses naming conventions and deduplication algorithms to identify when copies are needed versus when references to existing data suffice, thus maintaining accessibility while minimizing redundancy
3Speed
If datasheets are updated in place without version control, then update speed increases, but data consistency deteriorates with old and new versions coexisting
Solution Approach 1:
The patent implements preliminary versioning actions before updates occur. The data center automatically creates versioned copies of datasheets before modifications, assigns unique version identifiers, and maintains a version history. This preliminary structuring enables fast updates while preventing consistency issues, as the system is pre-configured to handle versioning rather than attempting to manage it during the update process
4Adaptability or versatility
If each sub-system manages its own datasheets independently, then sub-system autonomy is maintained, but data flow transparency decreases and quality control becomes difficult
Solution Approach 1:
The patent implements a feedback mechanism where the data center continuously monitors and records datasheet operations across all sub-systems. Metadata about data creation, modification, and access is automatically captured and fed back to the data center, which maintains a centralized view of data flow. This feedback loop preserves sub-system autonomy for local operations while providing transparent visibility into overall data quality and flow patterns
Data Source
AI summary
Embodiments of the present invention provide a method and an apparatus for data quality management and control. The method includes: receiving application information transmitted by a service sub-system; resolving datasheet operation trigger information to obtain datasheet flow information; receiving user information transmitted by the service sub-system and a target datasheet transmitted by the service sub-system; if a name of the target datasheet is different from a plurality of datasheet names corresponding to the service sub-system identifier, then instructing the service sub-system to store the target datasheet into a data center; if the datasheet operation information is updating a datasheet, instructing the data center to replace datasheet contents corresponding to the datasheet name with contents of the target datasheet.