Dagster

Dagster is a tool that helps organize and run your data workflows automatically. Think of it as a smart manager for all your data tasks. Instead of manually running scripts or remembering which files depend on others, Dagster handles this for you.

What makes Dagster different is how it thinks about data. It tracks your tables, files, and models as important items (called assets) rather than just focusing on the jobs that create them. This helps you see how all your data connects together.

The platform includes features for testing your code before it goes live, checking data quality automatically, and showing you how much your data processes cost. You can use it on your own servers or in the cloud through their managed service.

Getting started with Dagster is straightforward. Here are the main steps:

• Install Dagster using Python's package manager. Run a simple command in your terminal to get everything you need on your computer.

• Define your data assets by writing Python functions that describe what data you want to create and how to make it. Dagster uses simple decorators to mark these functions.

• Test locally before deploying. Dagster lets you run everything on your own machine to make sure it works correctly, which is much faster than testing in production.

• View in the web interface by starting the Dagster server. This gives you a visual way to see all your data assets, check their status, and understand how they connect.

• Schedule automatic runs to keep your data fresh. You can set up schedules or triggers that run your pipelines at specific times or when certain conditions are met.

• Asset-based data orchestration and tracking

• Local testing and development environment

• Automatic data quality validation checks

• Integration with dbt, Snowflake, and other tools

• Real-time data lineage visualization

• Built-in cost tracking and monitoring

• Schedule automation with smart triggers

• Python-native development experience

• Branch deployments for safe testing

• Built-in data catalog and metadata