Job runtime is a powerful metric. Datakin lets you to study how runtime changes over time, or how delayed jobs affect the rest of your pipeline.
Last week, Matt Turck and John Wu published their (mostly) annual report on the state of data, the 2021 Machine Learning, AI and Data (MAD) Landscape. We would like to share some observations of our own.
This initial release of Datakin includes features that will help you get a fresh perspective on your data pipelines, and quickly troubleshoot and repair any issues that might arise.
These foundations of communication and trust naturally created a culture that works for us, one where geography does not dictate opportunity. We feel empowered to act independently, making the best decisions for the company, and we check in with each other when we need support.
Often, datasets have built-in assumptions that aren't quite so obvious looking from the outside in. Datakin includes data quality metrics in the lineage graph so you can see your pipeline health from a distance.