In the previous blog , we explored normalization and denormalization as key concepts in logical data modelling and their impact on Salesforce data architecture. We reviewed the three primary normal forms (1NF, 2NF, and 3NF) and how they help reduce redundancy, enforce clear relationships, and maintain data integrity. Using examples such as Account and Address structures , we demonstrated how normalized designs separate related data into dedicated entities connected through

In the previous blog, we discussed the design strategy for architecting a data model that aligns with business needs, leverages Salesforce-native capabilities, and remains scalable as the system grows. A key part of this strategy is first aligning business entities conceptually and translating them into a logical blueprint. Only after the logical model is clearly defined should those entities be mapped to Salesforce constructs such as core data models for Sales and Service, s

In the previous blog, we explored data categorization — a foundational concept that must be mastered before moving into data model design. Categorizing data correctly shapes every architectural decision that follows. Designing a data model that aligns with business needs, leverages Salesforce-native capabilities, and remains scalable over time depends heavily on understanding these core design principles. As a Salesforce architect, your responsibility goes beyond configuring