📢 Announcing a webinar next week in collaboration with Noteable!
Fresh from PyData NYC, we are pleased to bring you this great session on debugging Notebooks:
Data engineers waste a lot of time troubleshooting long-running pipelines and know only too well the frustration of minor errors consuming hours of work. In this practical tutorial we will demonstrate an innovative solution for dramatically shortening testing cycles and reducing the number of reruns required, boosting developer/practitioner productivity, and reducing frustration on the team.
A productionalized notebook integrated with an orchestration platform provides an excellent balance of reproducibility, flexibility, and intent in a way that will be quickly consumable. This tutorial is valuable to data scientists and data engineers. This setup makes it easy to take notebooks from exploratory to production, but even easier to debug and ensure quality over time. This tutorial will show how you can achieve:
• Time-saving in initiating jobs: Allowing users to seamlessly transition an exploratory workflow created within a Noteable notebook, into a productionalized scheduled workflow in Dagster.
• Time and Cost Saving for debugging failed runs: Allowing users to immediately dive into a live running notebook at the point of failure, with all of the in-memory state preserved. This saves the users’ time, as well as saves companies’ compute costs by not requiring debugging to re-execute previous steps of the workflow.
Join Noteable’s CTO & Co-Founder *@Matthew Seal*and Elementl’s @jamie for this virtual event.