Model the underlying data architecture of the client environment, mapping entities, relationships, and the data flows that connect systems.
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Entity modeling
Define the core data objects that exist in the client environment (products, customers, orders) and how each is structured.
Relationship mapping
Document the relationships between entities across systems so integration complexity is visible before development begins.
Product data structures
Map product catalog structures, variants, and attributes, and trace how product data flows between commerce and source systems.
Customer data structures
Capture customer identity, segmentation, and profile data across CRM, commerce, and loyalty platforms.
Canonical data model design
Design a unified data model that reconciles structural differences between source systems and supports clean integration.
Integration field mapping
Map specific fields between source and target systems to validate transformation logic before integration development starts.
Entity relationship diagrams
Visual diagrams showing the relationships between core data entities across the client environment.
Canonical data models
A unified data model that reconciles structural differences between source systems and supports clean integration design.
Product data models
Structured maps of product catalog, variants, and attributes showing how product data is organized across systems.
Integration data maps
Field-level mappings between source and target systems that validate transformation logic before development begins.
“Most replatform failures occur when data models are not validated during discovery. Data Modeling Intelligence makes this step explicit and structured.”