Firstly an announcement – I’m moving jobs, from the start of January I’m very pleased to say I’ll be working at The Information Lab, one of the longest standing Tableau Partners in the UK and Tableau’s EMEA Partner of the Year they also very recently became Alteryx partners. I approached Tom, Craig and the team because they have clearly demonstrated a passion with Tableau that mirrors my own passion for Alteryx and, having got to know the ethos of the company and their values, then I’m very excited for what the future holds – for me, my new colleagues and also for Tableau and Alteryx.
All this has got me thinking about our role and how we describe what we do. For their part Alteryx coined the term Data Artisan to describe the people using their software; often those people without analyst in their name but those who find themselves needing to solve problems without the need for coding or IT departments. To be honest I never really got it, but with my new role I started considering the name again and considering my own situation with Alteryx and Tableau and it started to make sense.
For starts let’s look at what those words mean and their origin:
Data, “facts and statistics collected together for reference or analysis”, is the nominative plural of datum, originally a Latin noun meaning “that is given”.
Artisan (according to www.oxforddictionaries.com/) is a worker in a skilled trade, especially one that involves making things by hand. It has it’s origins in the mid 16th century “from French, from Italian artigiano, based on Latin artitus, past participle of artire ‘instruct in the arts’, from ars, art- ‘art'”.
Okay, so technically yes, being in a skilled trade working on facts and statistics for analysis or reference I can call myself a Data Artisan. More specifically my new role will involve instructing others in “the arts” and so this will also ring true.
So, I’m a Data Artisan technically – what about practically? Well let’s consider the tools of my trade:
Data – the raw materials / elements I work with
Alteryx – the tool of choice for data munging / data reshaping / data blending
Tableau – the tool of choice for data visualisation
The Dashboard – a representation of how the analysis looks that helps people understand the overall story
What about an Artisan’s tools of choice? Let’s consider a painter:
Paint – the raw materials / elements (s)he works with
Palette – the tool of choice for paint blending
Canvas/Brushes – the tool of choice for paint visualisation
The Painting – a representation of how the scene looked that helps people understand the overall story
…and like an artist a “Data Artisan” their skill in telling the story means the result becomes greater than the sum of it’s parts, and they can represent analysis in very different ways by skewing their visualisation towards their own view or political bias.
So looking at it this way then I’m left to think perhaps I am a Data Artisan after all…
As a final, perhaps fatal, push on the metaphor I’d like to ask…would an artist mix his paints directly on the canvas? Would an artist paint his picture on his palette? If you’re a Tableau or Alteryx user then there’s no need to compromise on the end result – make sure you’re being true to your art because Alteryx and Tableau used together are the only way to true masterpieces. [okay I got a tiny bit cheesy there but you get the idea!]
Having said all that I don’t think I’ll be calling myself a Data Artisan too often, I think Paul Banoub (The VizNinja!) said it best when he said:
“… call yourself whatever you want. Call yourself a Ninja, or a Jedi or a Yeti or a data rockstar. I don’t care. Just keep on pushing the boundaries and discovering. You should be proud of yourself for trying.” – Paul Banoub
In future my blogging efforts will be mainly on The Information Lab Blog but I will continue to add things to this blog on a less frequent basis, and will be reviewing the best of the Alteryx and Tableau community in regular posts here.
Thanks for reading.
As a tease, here’s the kind of thing you can create in Tableau if you mix your data in Alteryx first. Check in with the Info Lab in the New Year to find out how.