Name the business process and the AI proposes the fact table, its grain, and the dimensions around it, with columns and keys filled in
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Example
Prompt: “Star schema for retail sales: fct_sales at line-item grain with date, store, product, customer, promotion dimensions”
Paste your DDL, a database dump or a Prisma schema. Every table, column type, primary key and foreign key is read from the file itself, not guessed
Describe the business process and the AI draws the fact table with fully normalized dimension hierarchies, every lookup table and join path visible
Design professional data warehouse architectures showing ingestion, storage layers, transformation, and serving patterns
Describe the domain once and move between conceptual, logical, and physical views, the AI carries entities, attributes, and keys across each level
Common questions about ai star schema diagram generator
Yes, state the grain in the prompt ("one row per order line") and it lands as an annotation on the fact table. Ask for conformed dimensions across two facts and both fact tables will connect to the same dimension nodes, the way a bus-matrix design intends.
Tell it which dimensions are SCD Type 2 and it adds the effective_from / effective_to / is_current columns and notes the versioning strategy on the node, so the modeling decision is visible in the diagram rather than buried in a doc.
Generate the star version first, then ask the AI to snowflake a dimension (split product into product → subcategory → category) and you can see both shapes side by side before committing to one.
Export as PNG or JPEG for slides and docs, or embed a live link in Notion or a README that stays in sync when the model evolves, useful once the schema review starts producing changes.
Yes. Paste the CREATE TABLE statements (fact_ and dim_ prefixes, or Fact/Dim names) and the star is drawn exactly from them: the fact in the centre, dimensions around it, keys marked. Warehouse DDL without foreign keys gets its links from the key names, drawn dashed.
Name the source tables (VBAK, VBAP, KNA1, MARA, or Opportunity and Account) and the business process, and the AI proposes the fact grain, the dimensions, and a note mapping which source tables feed which fact.
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