Five Tenets for effective data visualization

Standard

Tenet is a principle honored by a group of a people. As a reader of this blog, you work with data and data visualization is an important element in your day-to-day work. So, to help you build effective data visualization, I created the tenets below which are simple to follow. This work is based on multiple sources and I’ll reference it below.

Five Tenets for effective data visualization:

  1. We will strive to understand customer needs
  2. We will tell the truth
  3. We will bias for simplicity
  4. We will pick the right chart
  5. We will select colors strategically

Examples for each tenet is listed below:

  • We will strive to understand customer needs

Defining and knowing your audience is very important before diving into the other tenets. Doing this will increase your probability of delivering an effective data visualization.

h/t to Mike Rubin for suggesting this over on LinkedIn here

  • We will tell the Truth

We won’t be dishonest with data. See an example below where Fox news deliberately started the bar chart y-axis at a non-zero number to make the delta look way higher than it actually is.

Source: Link

  • We will bias for Simplicity

3-D charts increase complexity for the end-users. So we won’t use something like this and instead opt for simplicity.

  • We will pick the right chart

I have linked some resources here

  • We will select colors strategically

Source here

Conclusion:

In this post, I shared five tenets that will help you build effective data visualization.

Data Culture Mental Model.

Standard

What is Data Culture?

First, let’s define what is culture: “The set of shared values, goals, and practices that characterizes a group of people” Source

Now building on top of that for defining data culture, What are set of shared values? Decisions will be made based on insights generated through data. And also, group of people represent all decision makers in the organization. So in other words:

An org that has a great data culture will have a group of decision makers that uses data & insights to make decisions.

Why is building data culture important?

There are two ways to make decisions: one that uses data and one that doesn’t. My hypothesis is that decisions made through data are less wrong. To make this happen in your org, you need to have a plan. In the sections below, i’ll share key ingredients and mental model to build a data culture.

What are the ingredients for a successful data culture?

It’s 3 P’s: Platform, Process and People and continuously iterating and improving each of the P’s to improve data culture.

How to build data culture?

Here’s a mental model for a leader within an org:

  1. Understand data needs and prioritize
  2. Hire the right people
  3. Set team goals and define success
  4. Build something that people use
  5. Iterate on the data product and make it better
  6. Launch and communicate broadly
  7. Provide Training & Support
  8. Celebrate wins and communicate progress against goals
  9. Continue to build and identify next set of data needs

Disclaimer: The opinions are my own and don’t represent my employer’s view.