Adaptive Filter for Data Consistency Probability
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Solution Overview
Problem
Large database systems face challenges in verifying the correctness of data entries, as incorrect data can be widespread and time-consuming to identify and correct, especially during data migrations from one system to another.
Innovation Solution
A system that uses a processor and interface to store data values along with their probabilities of certainty, based on consistency with previous data entries and time since update, employing an adaptive filter to automatically determine and adjust these probabilities, marking invalid data for correction and minimizing user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data in a large database is manually verified for correctness, then data accuracy is improved, but time consumption and operational effort increase significantly
Solution Approach 1:
The database system automatically verifies data correctness by comparing new data entries with previously stored consistent data without requiring manual verification. The system self-corrects inconsistencies by identifying and flagging potentially incorrect data based on consistency checks against historical records, thereby maintaining data accuracy while eliminating manual verification time
Solution Approach 2:
The system implements a feedback mechanism where data consistency is continuously checked against previously stored values. When inconsistencies are detected, the system provides feedback by marking the data as potentially incorrect and can automatically correct it based on the consistent historical data, ensuring ongoing data accuracy without continuous manual intervention
2Reliability
If data consistency checking is performed on every data entry, then data accuracy is improved, but system complexity and processing overhead increase
Solution Approach 1:
The system performs preliminary consistency checking by comparing new data entries against previously stored data before finalizing the data storage. This preliminary action identifies potential inconsistencies early in the data entry process, allowing for automatic correction or flagging before the incorrect data is committed to the database, thereby maintaining accuracy without requiring complex post-processing verification systems
3Reliability
If manual verification of data correctness is performed, then data accuracy is improved, but operational effort and resource consumption increase
Solution Approach 1:
The database system automatically performs data verification by comparing new entries with historical consistent data without requiring user intervention. The system self-identifies inconsistencies and can automatically correct them or mark them for review, thereby maintaining high data accuracy while minimizing operational effort to near-zero for routine verification tasks
Data Source
AI summary
A system for maintaining consistency of a data value using a probability includes an interface and a processor. The interface is configured to receive a data value for storing. The processor is configured to store the data value in a data element of a data structure and determine, using an adaptive filter, a probability of certainty associated with the data value. The adaptive filter receives a previously stored data value in a previously stored data element of a previously stored data structure as input to determine the probability of certainty associated with the data value. The adaptive filter provides as output the probability of certainty. The processor is further configured to store the probability of certainty associated with the data value in the data structure.