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Data as Code — Principles, What it is and Why Now?

No, DaC is not just versioning data! It’s applying the whole software engineering toolchain to data. For that, we need principles.

Sven Balnojan
Towards Data Science

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This post is part of a small series beginning with: Data as Code — Achieving Zero Production Defects for Analytics Datasets.

Image by Sven Balnojan.

Data as Code is a simple concept. Just like Infrastructure as Code. It just says “Treat your data as code”. And yet, after IaC appeared on the ThoughtWorks Radar in 2011, it still took roughly 10 years to “settle in” and is still on an uneasy spot where IaC advocates feel they need to remind people of the following:

“ …. Saying “treat infrastructure like code” isn’t enough; we need to ensure the hard-won learnings from the software world are also applied consistently throughout the infrastructure realm”

So much for that. Since I think we shouldn’t wait another 10+ years to get high-quality data applications fast, I wrote this article (series).

So what is DaC?

Data as Code: using the same good practices we learned in software and applying them to data in all

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