Data warehouse schema examples.
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What a data warehouse schema is.
A data warehouse schema organizes data for analysis rather than transaction processing. Its fact tables hold measurable events, such as sales or claims, while dimension tables hold the descriptive context used to group and filter those events.
A star schema keeps the fact table at the center with dimensions around it, making reporting relationships easy to see. The grain of the fact table—one sale, one claim, or one transaction—should be decided before choosing measures and dimensions.
- Standard
- Chen 1976 / Everest 1976 (crow's foot)
- Also follows
- Implements the crow's-foot subset
- Engine
- schematex-erd
- Editable
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Who uses data warehouse schemas.
Visits, users, products, referrers, and pages structured for clickstream reporting.
Claims joined to patient, provider, date, diagnosis, and procedure dimensions.
Transactions measured by date, customer, account, and product for reporting.
How to make a data warehouse schema in three steps.
Describe it
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Say what changes
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Common questions
What is a data warehouse schema?
A data warehouse schema is the structure used to organize data for analysis and reporting. It commonly separates event measures into fact tables and descriptive business context into dimension tables.
What is the difference between a fact table and a dimension table?
A fact table records measurable business events, such as an order amount or claim amount, plus keys to related dimensions. A dimension table describes the event with attributes such as date, product, customer, or location.
What is a star schema?
A star schema places one fact table in the center and connects it directly to dimension tables. It is a common warehouse design because the reporting paths are straightforward.
What is the grain of a fact table?
The grain defines exactly what one row represents, such as one order line, one daily account balance, or one insurance claim. Defining it first prevents mixing measures recorded at different levels of detail.
When should I use a snowflake schema?
Use a snowflake schema when dimensions need to be normalized into related tables, for example when a product dimension links to separate category tables. A star schema is often simpler to query and explain.
Other drawings for the same work.
Design a data warehouse schema.
Free account, no card. Describe the event, measures, and dimensions to model.
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