I wanted to share an interesting read from a couple weeks back. In his post, Elijah Meeks shares his thoughts on the data viz life cycle from end to end. Meeks’ focuses a bit on the product he and his company/team are working on, Noteable, as they try to “challenge the tool-centric and role-centric approaches we often see in data visualization which force a person to jump between tools or the artificially created walls of different roles.” 

Meeks walks us through the various discrete steps of data viz after pointing out that “[it’s] best to look at data visualization uncoupled from role or tool, and instead to focus on where it’s used in the process of working with data.” Let me briefly summarize each of this steps:

1. Exploratory Data Analysis - how do we understand the shape and pattern of the data?
2. Hypothesis Generation and Validation - what are the analytic questions and do the data support the underlying assumptions in different ways?
3. Exploratory Graphics - how do we actually explain the hypothesis testing and findings to an audience?
4. Productization - how are those exploratory graphics communicated?
5. Strategic Direction - how do we as an entire organization learn/grow from all steps above in the production of produced data viz? how does this promote our internal data literacy and best practices?

As a whole, our team touches on each of these pieces in the process, but as Meeks points out, these are largely siloed into different buckets/people and we are not thinking of the whole end to end data viz life cycle with most of our products. What can we do to think more holistically about data visualisation in its entirety?  For example, with productization, Meeks expands that this step is more than just about making a dashboard; instead “[productization] makes charts enhanced for collaboration (such as allowing commenting), easily shared, easily interactive, and automatically updated (or regularly published in the form of an email report)”. We have the dashboard bit down pat, so what can we do to future communicate our products and ensure the data (viz) are getting into people’s hands, it’s easy for them to understand, and hopefully, it’s actionable? 

Some food for thought. I would highly recommend reading Meek’s great article in its entirety and reflect how we incorporate the full data cycle into our work.

Happy plotting!