Real Estate Redefined: Optimizing Sales Processes with Salesforce

 

Objective: Streamlining Data Management and Reducing Costs. A comprehensive solution was developed to archive files from Salesforce to AWS S3 and transfer old records to Salesforce BigObject. The primary objectives were to:

• Efficiently move large files to AWS S3.
• Implement a robust system for archiving old data in Salesforce BigObject.
• Automate archiving tasks using Visualforce, Lightning Web Components (LWC), and Apex.
• Ensure seamless integration with storage services like GCP, Azure, and any REST API-compatible platforms.
• Provide users with an intuitive interface for easy access to archived files

Challenges:

Data Volume and Performance:

• Managing and transferring a high volume of large files while ensuring system performance.
• Archiving old records without impacting Salesforce storage capacity or operational efficiency.

Integration Complexity:

• Ensuring compatibility across multiple cloud storage providers, including AWS S3, GCP, and Azure.
• Designing scalable solutions to accommodate future data growth.

User Accessibility:

• Maintaining an intuitive experience for users accessing archived files and data.
• Avoiding disruptions to existing workflows during implementation.

Solution:

File Archiving to AWS S3:

1. User Interface: Visualforce and LWC pages were created to facilitate archiving operations, interacting with backend Apex controllers.
2. Apex Controllers: Developed to handle file transfer, AWS S3 authentication, and error handling.
3. Automated Archiving: Schedulable Apex classes automated regular file transfers, reducing manual efforts.
4. Linked Files: Ensured archived files remained associated with their Salesforce objects for a seamless user experience.

Data Archiving to BigObject:

1. Transfer Logic: Apex classes were built to transfer old records from Salesforce standard and custom objects to BigObject.
2. Automation: Schedulable Apex classes automated the archiving and cleanup of old records based on age and last modified date.
3. User Access: Provided access to archived data in BigObject without compromising performance.

Integration with Cloud Storage Services:

1. REST API Compatibility: Designed to work with AWS S3, GCP, and Azure through REST APIs.
2. Scalability: Developed a scalable architecture to handle increasing data volumes and diverse storage requirements.

Technology Used:

• Salesforce Apex: Developed custom controllers and schedulable classes for automation.
• Visualforce & Lightning Web Components (LWC): Created user-friendly interfaces for archiving operations.
• AWS S3: Implemented for file storage, leveraging its scalability and cost-effectiveness.
• Salesforce BigObject: Used for archiving and managing historical data.
• REST APIs: Enabled seamless integration with third-party cloud storage services.

Results:

Cost Optimization:

• Significantly reduced Salesforce storage costs by offloading large files to AWS S3 and archiving old data in BigObject.

Performance Improvements:

• Enhanced system performance by reducing the burden of large files and outdated records within Salesforce.

User Satisfaction:

• Maintained a seamless and intuitive experience for accessing archived files and data.

Versatility:

• • Delivered a flexible solution that integrates with multiple cloud storage providers, ensuring adaptability for future needs.

Conclusion:

This Salesforce-powered solution effectively addressed the challenges of managing large files and data. By leveraging AWS S3, BigObject, and advanced Salesforce technologies, the project delivered a scalable, cost-efficient, and user-friendly system. Its ability to integrate with multiple cloud providers ensures flexibility and long-term value for evolving data management needs.