On-Premise Data Migration via Mapping Rules
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Solution Overview
Problem
Enterprises face challenges in migrating on-premise data objects to on-demand data objects without losing legacy data due to differences in data structures between on-premise and on-demand applications, leading to potential data unusability with the new cloud-based systems.
Innovation Solution
The method involves retrieving mapping rules, extracting on-premise data objects, generating export and import files, and processing these files to map and transfer data from an on-premise database to an on-demand database, ensuring seamless migration and compatibility between the two environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data structures of on-demand application are used for migration, then cloud-based service adoption is enabled, but legacy data becomes unusable due to structural differences
Solution Approach 1:
The patent introduces mapping rules as an intermediary mechanism between on-premise data structures and on-demand data structures. These mapping rules translate and adapt legacy data to fit the new cloud-based structure, enabling both cloud adoption and legacy data preservation. The mapping rules act as a mediator that reconciles the structural differences between the two systems.
Solution Approach 2:
The patent applies parameter changes by transforming data parameters during migration through the mapping rules. The mapping rules modify data structure parameters, field mappings, and data format parameters to convert on-premise data into on-demand compatible formats while preserving the essential information content.
2Quantity of substance
If manual data migration methods are used, then data can be transferred between systems, but migration complexity and time consumption increase significantly
Solution Approach 1:
The patent implements self-service through automated mapping rule application. The system automatically retrieves appropriate mapping rules and applies them to migrate data without requiring manual intervention for each data transformation. This automation reduces migration complexity while maintaining comprehensive data transfer capability.
Solution Approach 2:
The patent applies preliminary action by pre-defining mapping rules in a rule repository before migration execution. These mapping rules are prepared in advance and stored for retrieval, allowing the migration process to simply apply predefined transformations rather than creating them during migration, thereby reducing complexity.
3Loss of information
If comprehensive data migration is performed, then all legacy data is preserved, but migration time and processing resources increase
Solution Approach 1:
The patent applies partial action by migrating only the data objects that are actually needed for the on-demand application to function. Rather than blindly migrating all possible data, the system identifies and migrates specifically the data objects required by the application, reducing migration time while preserving necessary legacy data.
Solution Approach 2:
The patent uses feedback mechanisms to identify which data objects are affected by the on-demand application. This feedback information guides the migration process to focus only on relevant data objects, optimizing the balance between data preservation and migration efficiency.
Data Source
AI summary
Methods, systems, apparatus, and computer programs encoded on computer storage medium for automatically migrating on-premise data objects used by an on-premise application to on-demand data objects used by an on-demand application including retrieving mapping rules corresponding to the on-premise data objects from a rule repository; extracting data corresponding to on-premise data objects that are affected during execution of the on-premise application, the on-premise application being executed within an on-premise computing environment, the data being stored in an on-premise database based on an on-premise database schema; generating an export file comprising the data; generating an import file based on the export file and the mapping rules, the import file comprising the data; and providing the import file to an on-demand computing environment that hosts the on-demand application, the import file being process-able by the on-demand computing environment to write the data from the import file into an on-demand database.