The Data Detective: Rules Nine + Ten and The Golden Rule

We’ve made it to the final chapters! As you read through Rules Nine and Ten as well as The Golden Rule, feel free to use this as a place to share your thoughts, questions, ideas, and reflections!

Remember that we’re all reading asynchronously, so if you aren’t caught up yet it’s not a problem! You can always post in the previous topics:

This book doesn’t necessarily need to be read in chronological order, so hop in on the chapters that interest you!

Chapter 9: Remember That Misinformation Can Be Beautiful Too

There are some real presentation masters out there, and they can sell almost anything. I will never forget a beautiful presentation that was filled with inaccuracies. I mentioned to a senior engineer that the pitch was beautiful. He looked at me and said, “It’s not about fonts, it’s about facts.” He was right. Alternatively, there are people who have excellent information but cannot deliver it in a digestible way. Since we all have biases, we need to work to see behind any glitz. Similarly, we also need to try to see key ideas that others may struggle to present.

Chapter 10: Keep an Open Mind

It is important to be humble and accept that there may be something we don’t know. That kind of self-awareness is difficult for many. Freeman Dyson (famous physicist) once said, “There are no prima donnas in engineering.” He clearly did not work at any of the companies I have.

The Golden Rule: Be Curious

Nature is a funny thing. When there is a problem, it frequently gives you hints that something is wrong. For example, the space shuttle Challenger had O-ring erosion during previous cold launches. No one followed up – they simply weren’t curious enough. The mission failure occurred when things got really cold. The biggest mistakes I have ever made involved me ignoring hints that there might be a problem. I was busy with other things. I often think of the statement by Isaac Asimov, “The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ but 'That’s funny …” Be curious. Follow up.

1 Like

this really resonated with me! both because I’m absolutely likely to be “taken in” by a beautiful presentation, but also because I’ve been on the other side, where as a data practitioner, showing information to colleagues with a non-data background has relied on some level of beautification.

I remember a particular instance where I was asked to come up with a visualization that would show effectiveness of after school programming between groups, so I did a simple black and white bar chart - only to be told that there was nothing convincing in the graph because it didn’t look nice! there’s definitely a balance to strike between making something look nice for stakeholders and going so far as to obscure information.