A Note About Leaving Comments...
Keep it practical. If you were training people for combat or MMA, how would you teach?
Thanks to everyone who leaves comments on the Practical Data Modeling articles. Your input is invaluable toward making this book the classic in data modeling. I appreciate anyone who leaves comments here.
A note about comments.
The book aims to equip someone from nothing to be functional in data modeling. This doesn’t make them expert, but they can do the “right things”, given their circumstances. Like in MMA and combat, everything is situational, and there’s no one-size-fits-all approach.
That said, some approaches are universally better than others. For instance, in MMA, rushing an opponent with your guard down and asking to get hit means getting hit, probably in laughably bad MEME-worth fashion. These are the career-ending moves this book will hopefully help you avoid. But that’s up to you. In data, being thoughtful and intentional about modeling your data from business requirements and data first principles is always better than ignoring these things.
Make sure your comments are aimed and worded at the people who know less than you. Use simple terms. Speak regular English. Avoid pedantic and overly complicated terms. Never assume people are at your level or understand what you’re talking about.
Don’t show off. A big reason why data modeling has failed and is dying as an official practice is it’s seen as being Ivory Tower. Practitioners don’t like “being talked down to.” They’re smart and busy. See the prior point, too, and this needs to be emphasized over and over. Your knowledge isn’t in the mind of the reader. This is why they’re reading this book. Support them on their journey. Remember, you were in their shoes long ago…
UPDATE (1/13/2025)
As much as I’d like for people to leave feedback and comments in one place, I get texts, social media messages, and random comments all over Substack. Going forward, feel free to leave comments if the intention is to discuss the material in a general sense. I definitely love the commentary and discussion, so keep it coming.
If you think you’ve found an ERRORS, please add them to this errata form. Having all of the errata in one place will help keep my focused organized on addressing potential errors, versus the high friction I’ve currently created for myself.
Again your feedback and comments are amazing. Keep them coming!
Thanks,
Joe
When I leave comments on the book, I'm leaving them for you, the author :) My thought process is that you've undertaken a massive challenge and I want to help and contribute.
The challenge with leaving comments is that one needs to be succinct, and context may be missed in that sense. Here's the computation as it happens in my mind: I read and process, and then formulate the point I'm trying to make. If I have to add in this mix the fact that someone (other than you, the author to whom the comment is intended) may not understand my language, then I may stop leaving comments all-together. I simply don't have that much computation power available.
My personal preference is to discuss these things live in a convo, where any ambiguities and missed context can be addressed on the spot.
Can you share career-ending data modeling moves from the field? I've seen less than optimal data model but none of them lead to such action.