Offline CRM Client Sync Using Local SQL Change Tracking
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Solution Overview
Problem
Existing customer relationship management systems, such as Salesforce SaaS, lack optimization for asynchronous interactions with mobile devices, particularly in offline modes, leading to inefficiencies in data synchronization and coherence between cloud and mobile applications.
Innovation Solution
A bidirectional synchronization algorithm and database organization method for CRM systems, utilizing a client local SQL database with shared singleton support tables and SQL transactions to maintain data coherence, supporting both online and offline modes, and employing a synchronization algorithm that ensures data consistency and integrity across cloud and mobile platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous synchronization is implemented between cloud CRM system and mobile device, then data consistency is improved, but network energy consumption increases
Solution Approach 1:
The system implements periodic synchronization instead of continuous synchronization, using change detection mechanisms to trigger sync operations only when data modifications occur. The synchronization algorithm compares change tokens or timestamps to determine if sync is needed, reducing unnecessary network transmissions and energy consumption while maintaining data consistency.
Solution Approach 2:
The system employs feedback mechanisms through change detection tokens and synchronization status tracking. The mobile device and cloud server exchange feedback information about data changes, allowing the system to intelligently determine when synchronization is necessary, thereby reducing energy consumption while ensuring data consistency is maintained.
2Reliability
If real-time synchronization is implemented between cloud CRM system and mobile device, then data availability is improved, but network dependency increases
Solution Approach 1:
The system performs preliminary actions by caching data locally on the mobile device before network availability changes. When the device goes offline, previously cached data remains accessible, and the synchronization queue preserves pending changes for later transmission, ensuring data availability without continuous network dependency.
Solution Approach 2:
The system provides beforehand cushioning through local data caching and synchronization queuing mechanisms. These buffers allow the system to operate independently of the network temporarily, cushioning against network unavailability while maintaining data availability and consistency upon reconnection.
3Loss of information
If full data synchronization is implemented between cloud and local databases, then data completeness is improved, but synchronization time increases
Solution Approach 1:
The system extracts only the necessary data changes for synchronization by comparing change tokens, timestamps, or version identifiers between cloud and local databases. Instead of synchronizing all data, it selectively transfers only modified records, reducing synchronization time while maintaining data completeness.
Solution Approach 2:
The system applies partial action by performing incremental synchronization rather than full data replication. It synchronizes only the subset of data that has changed since the last sync operation, significantly reducing synchronization time while ensuring complete data consistency through change detection mechanisms.
4Reliability
If frequent synchronization is implemented between cloud CRM system and mobile device, then data freshness is improved, but system resource consumption increases
Solution Approach 1:
The system implements periodic synchronization triggered by data change events rather than frequent time-based syncs. The change detection mechanism monitors for modifications and initiates synchronization only when necessary, maintaining data freshness while reducing system resource consumption by avoiding redundant sync operations.
Data Source
AI summary
Methods and systems for synchronizing a Customer Relationship Management (“CRM”) data system and its mobile application device version. The methods and systems enable both read and write access from the mobile device whether a network connection to the SaaS provider is available or not. They allow for effective local usage and intermittent synching without downloading large numbers of unnecessary records at each synch. The method and systems create a local mobile application device database version to track portions or all of the SaaS provider database. The methods and systems allow the mobile application to be functional while offline between synchs, including with incomplete data and metadata such as a database schema change. In one embodiment, multiple local database tables are used to represent a single SaaS CRM table to facilitate synchronization, and a status indicator is used to convey status on the mobile device application to the mobile user. Administrator settings enable the disclosed synching invention.