Kimball Dimensional Modeling · AI-Powered

What is DimBuilder?

DimBuilder is an AI-powered tool that converts your transactional SQL schema into a production-ready Kimball dimensional model in seconds. It generates the dimensional design, DDL statements, and a complete column mapping document — work that normally takes data engineers and architects days or weeks to produce manually.

Built for data engineers, analytics engineers, and data architects who need to move fast without sacrificing model quality.

How to use it

Paste your SQL schema

Copy your CREATE TABLE statements from your source system — PostgreSQL, MySQL, SQL Server, Oracle, or any standard SQL. DimBuilder reads the tables, columns, data types, and relationships.

Add context (optional but recommended)

Describe your business domain and what reports you need. For example: 'Monthly revenue by product category, top customers by lifetime value.' This shapes the model to your actual reporting needs.

Select your target warehouse

Choose Amazon Redshift, Snowflake, Google BigQuery, or Generic SQL. DimBuilder generates warehouse-specific DDL with the correct syntax and optimizations for your platform.

Get your dimensional model

In 30-60 seconds you have a complete dimensional model ready to review, download, and implement.

What you get

✓

Conceptual Model

Plain English description of your business process, entities, and relationships. Useful for stakeholder communication and documentation.

✓

Dimension Tables

Full dimension designs with SCD Type 1, 2, or 6 — whichever is appropriate. Includes surrogate keys, natural keys, SCD control columns, and 7 audit columns.

✓

Fact Tables

Fact table designs with precise grain definition, measures labeled with aggregation types (SUM, COUNT, NONE), degenerate dimensions, and both point-in-time and current foreign keys.

✓

DDL Statements

Production-ready CREATE TABLE statements for your target warehouse. Download as .sql files ready to run in your environment.

✓

Column Mapping CSV

Complete source-to-target mapping document showing every source column, target column, data type, and transformation logic. Download as CSV for documentation and ETL development.

✓

Business Questions

A set of specific business questions your model can answer, plus key metrics available for reporting — useful for validating the model with stakeholders.

Supported warehouses

Amazon Redshift

DISTKEY, SORTKEY hints

Snowflake

TIMESTAMP_NTZ syntax

Google BigQuery

TIMESTAMP syntax

Generic SQL

ANSI compatible

Common questions

What is a dimensional model?

A dimensional model organizes data into fact tables (measurements like sales, orders, events) and dimension tables (context like customers, products, dates). It's optimized for analytics and reporting — much faster and easier to query than transactional schemas.

What is Kimball methodology?

Kimball dimensional modeling is the industry-standard approach to data warehouse design, developed by Ralph Kimball. It defines patterns like star schema, slowly changing dimensions (SCD), and fact table grain that are used by data teams worldwide. DimBuilder applies these patterns automatically.

Do you store my schema?

No. Your schema SQL is sent to Anthropic's Claude API for analysis and is not permanently stored on our servers. Each request is stateless. Do not submit schemas containing real personal data or sensitive information.

What counts as one analysis?

One analysis = one schema submitted. You get the full dimensional model including all tabs (Overview, Conceptual, Dimensions, Facts, Mapping, DDL) plus the CSV download for that one submission.

Can I use the output in production?

Yes — but always review AI-generated output with a qualified data professional before implementing in production. DimBuilder produces high-quality models but AI can make mistakes. Treat the output as a strong first draft that saves you significant time.

What input do I need?

Standard SQL CREATE TABLE statements. DimBuilder works with any source — PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, or any system that uses standard SQL DDL. The more complete your schema (with primary keys and foreign key relationships), the better the output.

Ready to try it?

Start with 3 free analyses. No credit card required.