Data Science is Overrated, Here's Why
The author raises several valid situations where "data science" teams can be incorrectly used by their organization. One stood out, however, as it touched on when data scientists are hired without access to data - this forces them to build and maintain pipelines which many don't know how to do. If only they had a seamless data orchestration platform readily available... - John Forstmeier
A path towards a data platform that aligns data, value, and people
Petr asserts that instead of thinking about how your data moves through all the different layers of technology, you should think about how each step relates to the end user. By making this shift in mindset and structure of your data pipelines, you can simply your data pipelines into fewer steps while simultaneously gaining the ability to isolate steps that impact specific teams. The visuals in this article really make the point hit home. - Blake Burch
We Need to Know Our Data
Data (its collection and use) have posed many challenges for marginalized communities throughout time, however, it can also empower communities and make visible their struggles. Huberman has curated a collection interesting works at "intersection of data science and LGBTQIA+ communities". So, while this article is really a reading list, it is definitely worth a closer look. - Katt Baum
The Data Product Manager
It provides a unique perspective on the advantages of operating a data team with a product manager's roles and responsibilities. - Eric Elsken
Reinventing or Reusing?
In college, I learned how to write my own models to handle machine learning workloads. However, now that I am in the field, I am seeing that there is software out there that can take away some of the work needed to deploy a model. Vincent outlines the pros and cons of each side in this article well. - Steven Johnson