The practical trade-off
01

Wide: fewer joins and quick scenarios

02

Wide risk: duplication and divergent definitions

03

Star: reusable facts and dimensions

04

Star risk: modeling and relationship cost

05

Hybrid: core star plus governed consumption tables

Most teams do not need a binary choice

Wide tables can deliver one stable scenario quickly; star schemas support reuse, consistent dimensions, and governance. A common pattern is a core star model with governed consumption tables for individual agents or reports.

Wide tables pre-decide relationships

They simplify query context by materializing joins and derived fields, but copied tables can fork metrics and increase refresh cost. Declare source, grain, freshness, owner, valid questions, and prohibited combinations.

Star schemas preserve reusable relationships

Facts hold events while dimensions provide consistent customer, product, organization, and time views. Grain, keys, cardinality, and time relationships must still be explicit. BuildTable scale, connector, publication, and performance boundaries require POC confirmation.

Compare with the same question set

Test detail, aggregates, cross-dimension questions, historical change, and permissions. Compare modeling effort, query complexity, definition consistency, change impact, and review cost instead of one response-time sample.

Public references

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