Orchestration with Dagster. End-to-End Data Scientists. Snowflake's S-1. Experimentation @ Stitch Fix. [DSR #233]
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β€οΈ Want to support this project? Forward this email to three friends! π Forwarded this from a friend? Sign up to the Data Science Roundup here. This week's best data science articles Dagster: The Data Orchestrator In the status quo, traditional workflow engines such as Airflow work with a purely operational dependency graph: ensuring proper execution order, managing retries, consolidating logging, and so forth. These systems were a huge step forward over loosely coupled cron jobs and other solutions that did not formally define dependencies. A narrow focus on execution allowed those systems to be maximally general while demanding minimal change to the code that they orchestrated.
Orchestration with Dagster. End-to-End Data Scientists. Snowflake's S-1. Experimentation @ Stitch Fix. [DSR #233]
Orchestration with Dagster. End-to-End Dataβ¦
Orchestration with Dagster. End-to-End Data Scientists. Snowflake's S-1. Experimentation @ Stitch Fix. [DSR #233]
β€οΈ Want to support this project? Forward this email to three friends! π Forwarded this from a friend? Sign up to the Data Science Roundup here. This week's best data science articles Dagster: The Data Orchestrator In the status quo, traditional workflow engines such as Airflow work with a purely operational dependency graph: ensuring proper execution order, managing retries, consolidating logging, and so forth. These systems were a huge step forward over loosely coupled cron jobs and other solutions that did not formally define dependencies. A narrow focus on execution allowed those systems to be maximally general while demanding minimal change to the code that they orchestrated.