How to Explain Analytics Engineering to Friends & Family
I have been working as an Analytics Engineer for the past 17 months at a fast-paced consultancy. We deliver complex, end-to-end solutions to some of the biggest clients across telecommunications & retail. That’s the part I love.
The part I don’t love so much is how hard it often is for me to explain to my friends and family what it is that I actually do at work. Those who don’t work in tech equate every response to - “So, you work in IT”. That sounds fair to me, because generalization is at times quite useful. But, what if I told you its also equally hard explaining to my tech-y friends what analytics engineering is about? Most times, they just equate it to a data analyst or a data engineer. Meh!
There are obviously brilliant articles on the Internet about what an AE is such as the OG piece. But, “go read this article to know more” is not really an optimal solution when catching up on each other’s lives.
This article is dedicated to the analytics engineer who is looking for a better way to explain what it is that they do at work to their folks who don’t necessarily work in data.
- The Analytics Engineer is a choreographer who owns and synchronises movement of data between the data producers and data consumers of an organisation
- The Analytics Engineer day to day responsibilities revolve around understanding requirements, modelling data, analysing data sources, transforming data, testing data, documenting data and orchestrating these processes in end to end fashion
The Analytics Engineer is a Choreographer.
I am a fan of metaphors. And most people love them too. It’s one of those tools in the English language that make it easy to explain concepts. So here is my metaphor for an AE. An AE is a choreographer.
The modern data landscape is a fairly convoluted concept as it involves so many different moving parts. In fact, there are over 1400 companies trying to sell a part of the new data dream. With ruthless abstraction the entire data journey of any organisation can be likened to a dance. A dance between those that create the data and those that consume the data. Commonly called, the data…