The raw data tables Snowplow creates are a great starting point for analytics. Transforming the datasets into well structured, de-normalised tables - for example sessions or page_views - speeds up future analysis. With Dataform you can schedule and keep up to date the core Snowplow web model tables.
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.
Dataform’s built in SQLX functions enable us to infer dependencies and automatically build the dependency graph for your transformation pipeline.
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!
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.
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.