Which type of data model is ideal for ingesting into Data Cloud?

• A. Fragmented Data Model
• B. Hybrid Data Model
• C. Normalized Data Model
• D. Denormalized Data Model

Answer: (C)

Ingesting data into a data cloud is most effective when the incoming data is organized in a normalized form—each fact stored once, with relationships captured via keys. Normalization reduces redundancy, so updates, deletions, and consistency checks are applied in one place rather than across multiple copies. This yields a clean, canonical representation of core entities, which makes it easier to map data from diverse source systems, enforce data quality rules, and maintain accurate lineage as data flows into the cloud.

With a normalized structure, you can systematically integrate disparate sources, apply consistent business definitions, and manage changes without duplicating information. Once the normalized layer is established, you can create denormalized or analytics-optimized views later for fast querying, but the ingestion process itself benefits from a single, maintainable foundation. This is why a normalized data model is the best fit for bringing data into a Data Cloud.