Metadata Mapping for Automated Business Data Migration
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Solution Overview
Problem
Current data migration processes from source business systems to target systems, such as ERP systems, are manual, bespoke, and require custom scripting, making them time-consuming and resource-intensive, with no standardization or automation, and lack flexibility across different data structures and formats.
Innovation Solution
A computer-implemented method using a server system that automates data migration by generating source staging tables based on source metadata, creating mapping sets between source and target metadata, transforming data into a target structure, and loading it into target staging tables, eliminating the need for custom scripting and enabling flexible, repeatable data conversion across various systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual bespoke approaches are used for data migration, then mapping of each source to destination can be performed, but migration time and resource requirements increase significantly
Solution Approach 1:
The patent creates a universal data migration system that can handle multiple source systems and target systems through a common framework. The system uses standardized staging tables and mapping mechanisms that work across different ERP systems (SAP, Oracle, Microsoft Dynamics) and target systems (Oracle Cloud, SAP S/4HANA), eliminating the need for separate custom scripts for each migration scenario.
Solution Approach 2:
The system performs preliminary actions by pre-defining staging table structures and mapping relationships before actual data migration. The framework establishes standardized table schemas, data transformation rules, and mapping sets in advance, allowing rapid execution of migrations without time-consuming custom script development for each scenario.
2Adaptability or versatility
If custom scripts are developed for each data migration, then specific data transformation requirements can be met, but device complexity and resource requirements increase
Solution Approach 1:
The patent introduces staging tables as intermediary structures between source and target systems. These staging tables serve as a standardized intermediate format that simplifies data transformation by providing a common landing zone for all source data, from which it can be systematically mapped to various target systems without requiring complex custom scripts for each source-target pair.
Solution Approach 2:
The migration process is segmented into distinct, standardized components: source system extraction, staging table loading, mapping set application, and target system loading. This segmentation allows each component to be independently configured and reused, reducing overall system complexity while maintaining flexible data transformation capabilities.
3Adaptability or versatility
If manual data migration approaches are used, then customization for each company's specific needs is possible, but productivity and efficiency decrease
Solution Approach 1:
The system provides dynamic configurability through mapping sets that can be adjusted based on specific migration requirements. The framework allows companies to customize mapping relationships, data transformation rules, and staging table configurations without altering the core system structure, enabling both standardization for efficiency and customization for specific needs.
4Manufacturing precision
If bespoke migration scripts are created for each source system, then accurate data mapping can be achieved, but loss of time and increase in resource requirements occur
Solution Approach 1:
The patent uses copying by creating standardized templates for staging tables and mapping relationships that can be replicated across different migration scenarios. Once a mapping set is defined for a particular source system, it can be copied and adapted for similar systems, maintaining data mapping accuracy while eliminating repetitive script development work.
Data Source
AI summary
Computer-implemented methods and systems for migrating business data from source business system to target business system are described. The method performed by server system includes receiving request from user device to migrate source data from source business system to target business system and accessing source metadata associated with source business system and target metadata associated with target business system. The method includes generating one or more source staging tables based on source metadata. The one or more source staging tables include information of a plurality of source columns that is to be mapped. The method includes creating mapping sets for mapping source data to the target metadata, transforming the source data stored in the one or more source staging tables into a target data structure based on the target metadata, and loading a target staging table associated with target business system based, at least in part, on the transforming step.