Data Migration Application for Database Compliant Extraction
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Solution Overview
Problem
Conventional data migration tools require expertise and move data multiple times, leading to inefficiencies and increased costs when handling large data volumes, as they often necessitate complex user interfaces and multiple data transfers between servers.
Innovation Solution
A data migration method utilizing a two-stage data preparation and transformation system, where data is moved directly from source to destination databases with optimized bulk loading and transformation processes, minimizing data movement and leveraging standard SQL statements for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional ETL tools are used to migrate large volumes of data, then data transformation and loading can be performed, but data has to be moved multiple times between servers which increases cost and reduces efficiency
Solution Approach 1:
The patent extracts the transformation logic from the data movement process. Instead of moving data to a server and then transforming it, the transformation is performed directly on the source database using stored procedures and triggers, eliminating the need to move transformed data back and forth between servers.
Solution Approach 2:
The patent introduces staging tables as intermediaries within the destination database. Data is loaded directly into these staging tables from the source database, and then transformation occurs within the destination database environment, eliminating the need for intermediate server transfers.
2Adaptability or versatility
If conventional ETL tools with complex user interfaces are used, then medium to complex data transformations can be accomplished, but users must become experts in the specific ETL interface which increases complexity and reduces ease of use
Solution Approach 1:
The patent uses standard SQL statements and database triggers that are universally supported across different database systems. This eliminates the need for proprietary ETL interfaces while maintaining the ability to perform complex transformations through standard database operations.
Solution Approach 2:
The patent implements automated transformation logic through stored procedures and triggers that execute automatically during data loading. The system serves itself by performing transformations without requiring users to navigate complex interfaces or write complex transformation logic.
3Manufacturing precision
If data is moved from destination database to executing server for comparison and transformation, then proper data transformations can be made, but large amounts of data are moved from server to server which increases cost and time
Solution Approach 1:
The patent performs data comparison and transformation logic preparation in advance by creating stored procedures and triggers on the source or destination database. This preliminary setup eliminates the need to move data for comparison, as the transformation rules are already in place to execute automatically.
Solution Approach 2:
Instead of moving data to the server for transformation, the patent inverts the approach by bringing the transformation capability to the data itself through stored procedures and triggers that execute within the database environment, eliminating the need for data movement.
Data Source
AI summary
Data migration of large volumes can require large memory requirements and knowledge of complicated data migration tools. In one example, a data migration application may be initiated and a data volume may be identified to migrate from a source database to a destination database. The process may include deleting data currently stored in a staging table of the destination database, and transmitting the data volume from the source database to the staging table stored in the destination database.