Scalable analytics for data teams

Use one platform to manage data in your data warehouse, transforming raw data into trusted datasets to power your company’s analytics.
With Dataform, your entire data team can collaborate on a single platform and manage advanced workflows, all in SQL.

CREATE TABLE ...
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INSERT INTO ...
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ASSERT THAT ...
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GRANT SELECT ON ...
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Echo
Charlotte Tilbury
Trussle
Outshine

Prepare data for analytics across your entire company

With Dataform, build and schedule SQL workflows that transform raw data into reliable datasets ready for analysis, directly from your BigQuery, Redshift or Snowflake warehouse.

The Dataform platform

Dataform SDK

Develop reliable and scalable SQL pipelines
Open source. Run Dataform locally or anywhere.
Manage dependencies between your tables.
Reuse code across all your scripts.
Write tests to assert your data quality.
# Install Dataform CLI
npm i -g @dataform/cli
# Create new project
dataform init snowflake my_project
# Create new table
echo 'config { type: "table" } SELECT 1 as one'
> my_table.sqlx
# Run project
dataform run my_project

Dataform web

A complete solution for data warehouse management
Develop as a team in a collaborative web environment.
Version control all your code with a native GitHub integration.
Orchestrate your pipelines and get alerted if anything goes wrong.
Share a data catalog with all your data definitions.
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Connect your data warehouse in 5 minutes

Dataform integrates with Google BigQuery, Amazon Redshift, Snowflake, Azure SQL Data Warehouse and more

Google BigQuery
AWS Redshift
Snowflake
Azure SQL Data Warehouse

How Dataform works

1. Develop

Develop your transformations in SQL

Develop your data transformations in SQLX, Dataform’s open source language that makes SQL more reusable, flexible and organised.
Seamlessly create tables, define dependencies, add documentation and more.

Work as a team

Develop in a rich web IDE and share links with your team.
User can develop simultaneously from their own branches and isolated schemas.

2. Adopt software engineering best practices

Version control

Dataform integrates with Git via Github and other Git providers.
Each user can work from development environments to develop new tables without affecting everyone else.

Automate data quality testing

You can’t make informed decisions if you don’t trust your underlying data. Write tests against your input raw data and the output of data transformations, with issues triggering alerts before they hit your analytics.

Safe deployments

With Dataform, your team can deploy on isolated schema while developing and use CI/CD to integrate new changes safely.

3. Orchestrate

Scheduling made easy

Tell Dataform how often you want your datasets to update and it will do the rest.
Dataform builds a dependency tree (DAG) of all your datasets and makes sure your datasets are updated in the right order.

Notifications and logging

Dataform alerts you when potential errors error occurs and gives you detailed logs so you can fix issues quickly.

4. Use your data

Reliable data for your analytics

Use reliable and up to date datasets for all your analytical purposes.
All your data definitions are stored in a single repository, accessible by all your entire team.

Catalog your data and improve discovery

Catalog data across your Dataform project and your data warehouse for your entire company to find, understand and use to make data driven decisions.

What our customers say

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Benoit Machefer

Director of Data

If your business is scaling fast and you want to ensure data quality, make your life easier, leverage engineering best practices and remain BI tool agnostic then don’t hesitate to use Dataform for a second!
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Saadat Qadri

Analytics Practice Lead

Having modeled data using other tools in the past, this is much simpler and an easier environment to code in. The code compiles in real time and lets you know if there are errors in the syntax. It also helps generate a dependency graph for the data pipeline which is insanely useful.
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Will Misslin

Data Engineer

After using Dataform for a while I really discovered the power of integrating an IDE with an ETL tool. The web based IDE completely eliminates the hassle of maintaining local dev environments.
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