Your data warehouse's best friend
DataChonk is an AI-powered analytics engineering expert. It generates production-ready dbt models, proper tests, and comprehensive documentation — like having a senior AE on your team.
1-- Generated by DataChonk2with customers as (3select * from {{ ref('stg_stripe__customers') }}4)56select7{{ dbt_utils.generate_surrogate_key(8['customer_id']9) }} as customer_key,10customer_id,11email,12created_at13from customers// FEATURES
Everything you need to build great dbt projects
Stop wrestling with boilerplate. DataChonk combines AI expertise with dbt best practices to accelerate your analytics engineering workflow.
Chonk-First Architecture
Modular building blocks for your data warehouse. Source, Staging, Entity, Fact, Metric, Docs — each piece is reviewable and self-documenting.
Expert dbt Brain
An AI that actually understands dbt — from basic refs to advanced incremental strategies, semantic layer, and warehouse-specific optimizations.
Production-Ready Output
Generate complete dbt projects with proper structure, naming conventions, tests, and documentation that looks like a senior AE wrote it.
Package Intelligence
Smart recommendations for dbt_utils, dbt_expectations, elementary, and more. Know exactly why and where each macro is used.
Living Documentation
Auto-generated docs blocks, column descriptions, exposures, and governance notes. Your documentation stays in sync with your code.
Always Up to Date
Knowledge sync keeps DataChonk current with the latest dbt releases, best practices, and documentation changes.
// THE CHONK SYSTEM
Modular building blocks for your data warehouse
Each chonk is a distinct, reviewable unit of analytics engineering work. Think of them as Lego bricks for your dbt project.
Source Chonk
Define your raw data sources with freshness checks
What's Included
- Source definitions with database/schema
- Freshness configuration
- Column-level documentation
- Primary key tests
Output Path
sources/<source_name>.yml1version: 223sources:4 - name: stripe5 database: raw6 schema: stripe_prod7 freshness:8 warn_after: {count: 12, period: hour}9 tables:10 - name: customers11 columns:12 - name: customer_id13 tests: [unique, not_null]// EXPERT-LEVEL OUTPUT
Code that looks like it was written by a senior AE
DataChonk generates production-ready dbt code with proper incremental strategies, surrogate keys, and warehouse-specific optimizations. Every model includes comprehensive tests and documentation.
Supported Warehouses
1{{2 config(3 materialized='incremental',4 unique_key='order_key',5 incremental_strategy='merge',6 on_schema_change='append_new_columns'7 )8}}910with source as (11 select * from {{ ref('stg_shopify__orders') }}12 {% if is_incremental() %}13 where updated_at > (14 select coalesce(max(_loaded_at), '1900-01-01')15 from {{ this }}16 )17 {% endif %}18),1920transformed as (21 select22 {{ dbt_utils.generate_surrogate_key(['order_id']) }} as order_key,23 order_id,24 customer_id,25 total_amount_cents / 100.0 as total_amount,26 order_status,27 updated_at as _loaded_at28 from source29)3031select * from transformedReady to build better dbt projects?
Start generating production-ready analytics code with expert-level documentation and testing. Your data warehouse will thank you.
