Evaluating Salesforce Data Migration Strategies: A Comparative Study of Traditional ETL and Salesforce Data Cloud

Salesforce data migration plays a vital role in enabling organizations to successfully adopt Salesforce as their primary Customer Relationship Management (CRM) platform.Selecting the right migration approach is crucial to ensure data accuracy, system performance, and longterm scalability.This paper presents a comparative study of traditional Extract-Transform-Load (ETL) methods and Salesforce Data Cloud as two distinct approaches to Salesforce data migration.Traditional ETL tools focus on batch-based data movement with extensive preprocessing outside Salesforce, while Salesforce Data Cloud provides a native, real-time, and unified data integration framework within the Salesforce ecosystem.The study evaluates both approaches based on key factors such as data complexity, transformation capabilities, implementation cost, scalability, and maintenance effort.Case examples from the financial services, retail, and healthcare sectors are used to demonstrate practical migration scenarios and decision-making considerations.The paper concludes with key insights to help organizations select an appropriate migration strategy aligned with their business needs, data volume, and digital transformation goals.