LINCOLNINST.EDU

SQL to Salesforce Migration with Data Normalization and Ontology Mapping

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847K

Records Migrated

100%

Data Integrity

Years of Data

Business Days Lost

The Challenge

The Lincoln Institute of Land Policy had accumulated 15 years of critical institutional data in aging SQL Server databases — donor records, grant histories, research publications, event attendees, and constituent relationships. The legacy system was becoming unmaintainable, and staff were working around data quality issues that had accumulated over years of manual entry. The migration to Salesforce had to preserve 847, 000+ records with 100% data integrity, clean and deduplicate messy historical data, map complex legacy relationships to Salesforce's object model, and enable the organization to keep working throughout the transition.

The Solution

We designed a phased migration approach with a custom Python ETL pipeline. Phase one involved deep analysis of the legacy schema — mapping 127 tables to Salesforce standard and custom objects, identifying data quality issues, and building deduplication rules based on fuzzy matching algorithms. The migration pipeline ran incremental syncs during development, allowing parallel validation against production data. Custom Apex triggers and flows replicated legacy business logic in Salesforce. A staged cutover plan allowed departments to migrate sequentially, with fallback capability to legacy systems for 30 days post-migration. User training ran parallel to technical work, ensuring adoption from day one.

Legacy Migration

15 years of SQL Server data

Data Cleansing

Deduplication & normalization

Salesforce Integration

Custom objects & workflows

Change Management

Staff training & adoption

Our Approach

Step 1

Assessment & Mapping

Analyzed 127 legacy tables, mapped to Salesforce object model, identified 23,000 duplicate records requiring merge rules, and documented all business logic for replication.

Step 2

ETL Pipeline Development

Built Python extraction layer, implemented fuzzy matching for deduplication, created transformation rules for data normalization, and established incremental sync capability.

Step 3

Salesforce Configuration

Built 12 custom objects, 47 custom fields, automated workflows via Flow, and Apex triggers to replicate legacy business rules. Integrated with existing email and document systems.

Step 4

Migration & Training

Executed staged department-by-department migration, conducted 8 training sessions with 45 staff members, maintained legacy fallback capability, and validated 100% data integrity.