Cloud-native data architectures for Salesforce integration: harnessing ML and Agile approaches for scalability
Keywords:
Cloud-native data architecture, Salesforce integration, machine learning, microservices, serverless computing, API performance, predictive analytics.Abstract
The integration of Salesforce with enterprise applications has become a critical requirement for organizations seeking scalable, real-time, and resilient data architectures. Traditional monolithic integration approaches often fail to meet the performance, agility, and security demands of modern enterprises. This study explores the role of cloud-native data architectures, particularly microservices, serverless computing, and machine learning (ML), in optimizing Salesforce integration.
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