Data Migration System Prioritizing Frequent Usage Patterns

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Solution Overview

Problem

Current data migration technologies lack a comprehensive analysis of relevant data, leading to the selection of irrelevant data for migration and the exclusion of important data, requiring extensive knowledge of the operational flow and functionalities of the legacy platform.

Innovation Solution

A system that determines frequently used relevant data by analyzing usage patterns in legacy platform log files, database access files, and memory dumps, assigning migration priorities based on frequency of occurrence, and automating the data migration process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a system developer manually investigates the design and operational flow to determine data for migration, then the accuracy of data selection is improved, but the time and resource requirements increase significantly

Engineering Contradiction:

Improvedata selection accuracyVSAvoiddata migration planning time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-analysis by automatically investigating its own design and operational flow through log file analysis, database access pattern examination, and usage frequency measurement. This eliminates the need for external developer investigation while maintaining high data selection accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical process of developer investigation is replaced with an automated computational system that uses log analysis, database querying, and algorithmic determination of data usage patterns. This substitution dramatically reduces time requirements while preserving accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Quantity of substance

If all accumulated data is migrated from the legacy platform, then data completeness is improved, but the processing power and time requirements increase significantly

Engineering Contradiction:

Improvedata volume migratedVSAvoidprocessing power consumed

Core Design Contradiction:

Quantity of substanceVSUse of energy by moving object

Solution Approach 1:

The system extracts and identifies only the relevant subset of data that is actually used by the legacy platform through log analysis and usage pattern detection. Irrelevant data is excluded from migration, reducing the total data volume while maintaining data completeness for operational needs.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Different data subsets are assigned different migration priorities based on their usage frequency and importance. Frequently used data is marked for migration with high priority, while rarely used data is excluded or marked for later migration, optimizing resource allocation.

Inventive Principle:

Principle #3Local quality

3Measurement precision

If comprehensive analysis of data usage is performed to select relevant data, then the relevance of migrated data is improved, but the device complexity increases

Engineering Contradiction:

Improvedata relevance accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses a unified multi-functional approach that combines log file analysis, database access pattern examination, and usage frequency measurement into a single comprehensive analysis engine. This universal system handles multiple analysis tasks without requiring separate complex subsystems.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces an intermediary analysis layer that processes raw log files and database access patterns into structured usage information. This intermediary layer simplifies the complexity by providing a standardized interface between the legacy platform and the migration decision-making process.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Device complexity

If manual data selection is performed without comprehensive analysis, then the system complexity is reduced, but the accuracy of data selection deteriorates

Engineering Contradiction:

Improvesystem complexityVSAvoiddata selection accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11360952B2System and method for managing data migration based on analysis of relevant data

Publication Date: 2022.06.14 BANK OF AMERICA CORP

AI summary

A system is configured for managing data migration from a legacy platform to a target platform is disclosed. The system determines relevant data for the data migration. The system determines frequently used relevant data, where the relevant data is determined to be frequently used when the relevant data is used more than an occurrence threshold number in a particular time period by the legacy platform. The system assigns a migration priority to the frequently used relevant data based on its frequency of occurrence. The system migrates the frequently used relevant data from the legacy platform to the target platform.