Table of Contents

Data Migration

During data migration, it's recommended to follow this flow:

1. Data Extraction & Data Cleaning

   • Connect the system to your ETL (Extract, Transform, Load) tool.
   • Clean, Deduplicate, Enrich, and Standardize data.

2. Data Transformation & Verification

   • Transform data to fit the Salesforce Schema.
   • Define External IDs for proper data mapping.

3. Data Loading

   • Group records by parents to avoid record locking during insertion.
   • Temporarily disable sharing settings.
     • Disable Flow, Trigger, and automation.
     • Enable defer sharing (Contact Salesforce).
   • Utilize Bulk API 2.0 for efficient parallel data loading.

4. After Load

   • Re-enable sharing settings.
     • Enable Flow, Trigger, and automation.
     • Disable defer sharing (Contact Salesforce).
     • Recalculate sharing settings.
   • Perform data integrity verification.

Artefact

Migration Approach

1. Big Bang Migration

• Description: All data is migrated in a single, large event.
• Pros:
• Simpler to plan and execute
• Shorter transition period
• Cons:
• High risk
• Long downtime
• Potential for significant issues if something goes wrong

2. Phased Migration (Incremental)

• Description: Data is migrated in phases or batches over a period of time.
• Pros:
• Lower risk
• Easier to manage
• Less downtime
• Cons:
• More complex to plan
• Potential for data consistency issues between old and new systems

3. Rolling Migration

• Description: The migration is performed in a continuous, sequential manner, often across different segments or parts of the system. The process rolls through different parts of the data or system in succession.
• Pros:
• Minimal downtime
• Reduced risk
• Flexibility to make adjustments during the migration
• Cons:
• More complex to plan
• Resource-intensive
• May require additional resources to manage overlapping operations