Data never stays in one place for long. Any business or team that works with data needs to be thinking about how data moves from one place to the next. This often happens multiple times, continuously, and in multiple different streams. The conce...

maestro 0.3.0 introduces principled methods for obtaining a schedule table, pipeline status, and artifacts (i.e., return values). This is now possible because of a major refactoring of the backend to use R6 classes for pipelines and schedul...

maestro 0.2.0 brings with it new features for scheduling pipelines on specific hours, days, or months. With a few new tags, we have so much more versatility for scheduling. If you haven’t heard of maestro, it’s a package that helps you sche...

In the previous post we saw how maestro helps orchestrate data pipelines in a single R project. For maestro to be useful you need to deploy it somewhere and these days that ‘somewhere’ is often cloud-based. Here we’ll walk through deploying a m...

I’m thrilled to announce the release of maestro, a new package for developing, scheduling, and monitoring data pipelines. Here, I’ll walk through what maestro does and why you’d want to use it. install.packages("maestro") The Motivation ...