“Everything starts out looking like a toy” (No.1)
A newsletter of small observations affecting the intersection of data and systems.
Welcome! I am using this letter to share a few things. This is the origin story (edition No.1), coming at you on July 4, 2020.
This Week’s Idea
I’ve been thinking about The Abilene Paradox. If you’ve never heard of this before, it’s a parable describing how teams working on a project sometimes end up in a place no one wanted to go. What matters about this? When working on a group project, it’s critical to identify the WHY (reason for doing the project) and not to skimp on the HOW (way we get to a satisfactory conclusion), and to make sure they are in the right order.
Links to Read and Share
These are links that caught my eye.
1/ Associative links to things. Shape Matrix is a method of taking a unique signature and embedding it into a mathematical shape, kind of like a nerdy QR code. This is cool because it provides many new ways to encode data visually. It also is a promising way (by showing initial and subsequent shapes) to demonstrate how data is transformed from a root set into a new form.
2/ A History of House Numbers - Thanks to Flowing Data, I learned about this quest to catalog all of the house numbers in one zip code. Using Zip Code as a bucket reminds us of the way you can standardize information and make it possible to compare very unlike objects (different houses with different families) through a common identifier (numbers they share). It’s also a good reminder of the importance of standard classification in a data set. Thank you Postal Service!
3/ Making spreadsheets faster - If you use Google Sheets, you might find they are … slow when you get into a large number of cells and rows. Ben Collins shares how to use BigQuery in Google Sheets, which opens up the world of large data sets to Google Sheets. It’s no panacea, but opens the possibility of using Sheets as a data viewer and not just a temporary data repository.
What to do next
Hit reply and let me know if you’ve got links to share, data stories, or want to say hello.
You’re at the end. Thanks for reading! I’m grateful you found this.
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Want longer-form ideas? Check out on Data Operations or other writings at gregmeyer.com.
The next big thing always starts out being dismissed as a “toy.” - Chris Dixon
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