Core Service

Data Modeling

Data modeling creates structured schemas for enterprise warehouses so heterogeneous data stays organized, reliable, and scalable.

Definition and Function

Data modeling defines how enterprise data is structured, often with methodologies like Data Vault (Hubs, Links, Satellites), so diverse sources can be integrated predictably.

Benefits

It provides scalable, flexible architecture that adapts quickly to source-schema changes while protecting long-term warehouse integrity and reliability.

Measurable Savings and Revenues

Automated schema modeling can reduce development time by about 75%, shrinking work from one day to roughly two hours per source. This drives lower labor cost, faster deployment of data assets, and better resource allocation through pre-deployment visibility into storage impact.

How data modeling works Animated flowchart: inputs feed into logical and physical data modeling stages, producing a logical model, physical model, and final data. Process models Data requirements Technical requirements Performance requirements Business data Logical data modeling Physical data modeling Create / update data Logical data model Physical data model Data

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Data Integration Data Modeling Reports and Dashboards Data Governance