CRM Data Migration Wizard for Cloud Testing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy on-premise CRM systems face challenges in feature upgrades and maintenance compared to cloud-based systems, necessitating a simplified method for data migration to cloud-based solutions.
Innovation Solution
A CRM migration system using a wizard that allows users to select and export business objects and records to external cloud-based storage, enabling rapid evaluation and minimalistic data set migration, including the creation of CSV files and filtering criteria for efficient data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full dataset migration is performed from legacy CRM to cloud-based CRM, then complete data availability is achieved, but complexity and cost of migration increase significantly
Solution Approach 1:
The patent segments the migration process into distinct phases: identification of critical data elements, extraction of selected records, transformation to target schema, and loading into cloud-based CRM. This segmentation allows organizations to migrate only essential data initially rather than attempting to move entire datasets, reducing migration complexity while ensuring critical data availability.
Solution Approach 2:
The patent applies partial action by enabling migration of a representative subset of data (e.g., 10-20% of records) that captures the essential business scenarios and data relationships. This partial migration is sufficient for validation and testing purposes, avoiding the complexity and cost of complete dataset migration while still achieving the goal of verifying data availability in the new system.
2Device complexity
If representative data subset is migrated for testing, then evaluation complexity is reduced, but data completeness for full system evaluation is limited
Solution Approach 1:
The patent applies local quality by ensuring that the selected representative subset contains diverse and varied data that reflects different business scenarios, customer types, and data relationships. Rather than migrating random or uniform samples, the system strategically selects records that locally represent the broader data population, maintaining information completeness for evaluation purposes while keeping the overall dataset size manageable.
Solution Approach 2:
The patent employs preliminary action by performing data analysis and selection before migration to identify and extract the most representative records. This pre-migration preparation includes defining selection criteria, validating data quality, and ensuring the subset adequately represents the source system's data characteristics, thereby reducing evaluation complexity while preserving necessary information completeness.
3Stability of the object's composition
If legacy CRM system is maintained on-premise, then existing operations continue without disruption, but feature gap widens compared to cloud-based systems
Solution Approach 1:
The patent applies dynamics by enabling a gradual, phased migration approach rather than forcing an immediate complete transition. Organizations can dynamically adjust their migration pace, starting with critical data and progressively moving additional datasets as validation succeeds. This dynamic approach maintains operational stability during the transition while progressively closing the feature gap by enabling adoption of cloud-based CRM capabilities.
Solution Approach 2:
The patent uses data migration as an intermediary mechanism that bridges the legacy on-premise CRM and the new cloud-based system. By establishing this intermediate data transfer layer, organizations can maintain their existing operational workflows on the legacy system while progressively adopting cloud-based features, thus preserving operational stability while improving feature currency over time.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for extracting customer relationship management (CRM) data from an on-premises database for testing with a cloud-based CRM. The extraction approach simplifies, through the use of a wizard, the selection of relevant customer records and their extraction, along with any dependencies on other records. The extracted records can then be uploaded to the cloud-based CRM for evaluation.