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Organizing Data Teams — Where to Make The Cut

There are four ways to decentralize and structure data teams. Learn how to choose the right one.

Sven Balnojan
Towards Data Science
7 min readDec 16, 2020

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(The four typical data team organization forms. Image by the author.)

Introducting Data Organizations

Data organizations within companies look like snowflakes. From close up, they are all unique, but if you step back, they all kind of look alike. They all deal with data and are usually organized around some data or analytics department.

That makes it hard to make organizational changes because it’s really hard to see the overarching picture. I like to propose a simple viewpoint that might make this easier.

I think these snowflakes come in four snowflake buckets. And really only one feature distinguishes them: Where in your data flow do you make the cut and go from a central unit working on the data to multiple decentralized ones, embedded into other units.

Let’s highlight that using a bunch of examples from the great survey article fishtown analytics provides, as well as some additional cases.

The Centralised One Man Show

Companies usually start out with the one-man show. One to two data scientists in a data team that handles “everything…

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Towards Data Science
Towards Data Science

Published in Towards Data Science

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Sven Balnojan
Sven Balnojan

Written by Sven Balnojan

Head of Product at MAIA | PhD, ex Head of Mkt | Author | AI & Data Expert | Newsletter at http://thdpth.com/

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