The modern data stack (MDS) is the defining paradigm informing how new organizations use technology to leverage data. Lots of digital ink has been spilled, and takes are growing ever spicier on all things MDS. Here’s a more benign one:
The Modern Data Stack currently focuses too much on tooling and would be more effective if it refocused on the humans using the tools. In particular, the MDS ecosystem doesn’t currently address implementation,
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In the past few years, much has been written about problems like discoverability, observability, data quality, and the need for data teams to become more “engineering oriented” in their mindset.
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There’s been a lot of discussion lately about systems for doing version control for data. Most recently, Ryan Gross wrote a blog post “The Rise of DataOps” where he
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The landscape of the data and analytics world is shifting rapidly. In many companies, the roles and responsibilities of data engineers, analysts, and data scientists are changing. This change has
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I have spoken to many fellow analytics practitioners who are adament that they want their team to never touch “production.” While there are good reasons to be careful whenever you make changes
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Often, Data and Analytics teams go under-utilized in their organization because they can not collaborate effectively with the broader Technology and Software Engineering teams.
By designing software following the “code
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