The data modeling platform for Stitch Data

The data modeling platform for Stitch Data

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Stitch is a simple but powerful ETL service for businesses of all sizes, from startups to large enterprises. Replicate and integrate data from more than 100 data sources into BigQuery with only a few clicks. Then use Dataform to transform and combine the separate data sources into a single source of truth for your business.

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Model your data into a shareable catalog

A single source of truth is only helpful if it’s accessible. Dataform automatically turns your transformation code into a shareable data catalog, giving business users and other analysts visibility into your data model.

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Version control your SQL

The Dataform web IDE is natively integrated with GitHub and GitLab. Version controlling your SQL has never been easier: create branches, commit changes, revert files and create pull requests without ever needing to touch the command line.

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Intuitive dependency management

Dataform’s built in SQLX functions enable us to infer dependencies and automatically build the dependency graph for your transformation pipeline.

Kaleva
Livup
Echo
Charlotte Tilbury
Acordo Certo
Big Tree
Teatime Games
Slite
Tasman Analytics
Butternut Box
Outshine
Dreamdata
Mittelbayerische
SME Capital
Mixcloud
Rapidoo
Prolific
Unbound Solar

Learn more about the Dataform data modeling platform

Dataform brings open source tooling, best practices, and software engineering inspired workflows to advanced data teams that are seeking to scale, enabling you to deliver reliable data to your entire organization.

What our customers say

Mike Lee

Head of Data

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Being able to produce analytics tables that we are confident in the output of (because of assertions) and are as up to date as we need them to be (because of scheduling) makes our lives really easy. The UI is incredibly easy and intuitive to use, meaning we spend little of our time setting these things up, and most of our time writing SQL!

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Jim Lumsden

Growth Analyst

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I love the dependency tree in Dataform. For me this is a central place for sanity checking my data flows, understanding if I'm reimplementing a dataset which already exists, and verifying logic. Secondly, I love SQLX for generating SQL of a similar structure again and again, it really speeds up development and let's your abstract away logic.

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Saadat Qadri

Analytics Practice Lead

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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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