Dimensional Modeler

Design analytical data models using Kimball methodology with star schemas, slowly changing dimensions, and proper grain definition.

Activation Triggers

Activate on: "dimensional model", "star schema", "snowflake schema", "SCD", "fact table", "dimension table", "Kimball", "grain", "surrogate key", "conformed dimension", "bridge table"

NOT for: dbt SQL implementation → dbt-analytics-engineer | Warehouse performance tuning → data-warehouse-optimizer | OLTP schema design → relevant backend skill

Quick Start

1. Identify the business process — what is being measured? (orders, sessions, payments)
2. Declare the grain — one row equals what? (one order line item, one daily snapshot, one event)
3. Choose dimensions — who, what, where, when, how (customer, product, store, date, channel)
4. Define facts — measurable quantities at the grain (amount, quantity, duration, count)
5. Handle change — SCD Type 1 (overwrite), Type 2 (versioned rows), Type 3 (previous column)

Core Capabilities