Joe's Nerdy Weekend Reads #6
It's the weekend, so time to unwind. Pour a cup of coffee (or many) and enjoy some interesting reading.
Happy Saturday!
In this morning’s Practical Data Modeling community discussion, we shared perspectives and approaches for getting buy-in for data modeling. You wouldn’t think this is something where you need to get support or buy-in. But, like many things, different stakeholders have different views on what’s important. And data modeling means different things to different people.
This discussion highlights that no two organizations or situations are the same. While data modeling as an adopted practice might be a no-brainer at some companies, other companies adopt a more carefree approach. Some practitioners may not even be aware that data modeling is a thing that people do (I’ve seen this), nor the various techniques and approaches.
Summarizing some of the highlights of the conversation, getting buy-in for anything, data modeling or otherwise, is about a few things.
First, be able to articulate the value of what you’re proposing. This might be the numerical value of something (ROI, TOC, etc). Taking it a step further, it’s also about showing other people what’s in it for them. Too often, people try to get buy-in from others from a place of selfishness and lack of empathy. This is almost always a mistake. People usually don’t want more work on their plate, especially when the benefit to them isn’t clear. Instead, show people how a better data model will improve time to better decisions, insights, and actions.
Second, most people probably don’t care about data modeling. Data isn’t top of mind for most people, even though organizations are supposedly “data driven” these days. You need to speak in terms that people understand and care about and meet people where they are. Don’t use terms like “normalization” or “surrogate key” to people who won’t know what these mean. If it’s helpful, use diagrams of how various data in your organization relate to each other and to business processes. Make things very simple and approachable. Buy-in is more likely when people understand what they’re asked to buy into.
Finally, the latest AI hype cycle means you’ve got a good opportunity to do the data housekeeping you’ve always wanted to do. I’m guessing a better data model is one of these. With seemingly every board and CEO fixated on how their company can become AI-driven, educate stakeholders on why good data means AI that serves the business. If there’s ever a time to move on building your data and AI foundation, now is the time (especially before the hype cycle bursts).
Watch here:
We ended the discussion by discussing our next community event. We’re thinking of doing a “data therapy” session where we gather around and “let it all out.” I think this would be healthy for the data community, as I sense a lot of pent-up frustration when I listen to practitioners and leaders. If this interests you, leave a reaction or drop a comment.
I’m off to the snowy Wyoming mountains this weekend and then to the sunny Mediterranean coast next week. Yes, I know these are almost polar opposite places.
Hope you have a fun weekend!
Thanks,
Joe
P.S. If you want to take your data career to the next level, check out my upcoming course with
. Starts June 17th. Get a 25% discount here.If you haven’t done so, please sign up for Practical Data Modeling. There are lots of great discussions on data modeling, and I’ll also be releasing early drafts of chapters for my new data modeling book here. Thanks!
Cool Weekend Reads
“The world's second-largest private employer employs 1.5 million people. While that's a lot, it's a decrease of over 100,000 employees from the 1.6 million workers it had in 2021. Meanwhile, the company had 520,000 robots in 2022 and 200,000 robots in 2019. While Amazon is bringing on hundreds of thousands of robots per year, the company is slowly decreasing its employee numbers.”
This is the true use case for AI, in my opinion. While stuff like ChatGPT is nice, the game changer is AI and robots in the real world, doing real-world things. It’s also going to cause a massive dislocation for the middle and lower class. As the US continues to become more polarized and people are increasingly dislocated from these “undesirable” jobs, I’m concerned about the social ramifications.
Boeing and the Dark Age of American Manufacturing (The Atlantic)
WTF happened to Boeing? When I was a kid growing up in the 1980s, Boeing was the pinnacle of American manufacturing. They made awesome airliners and bombers. As I learned more about the history of Boeing, I realized it was the victim of the Jack Welch-ification of American business. Instead of being an engineering-led company (you’d hope aircraft has an engineering and quality focus), Boeing succumbed to “delivering shareholder value,” which meant expediently chopping away at the things that made Boeing great and outsourcing them to third parties. The result? A loss of engineering competency, a company run not from the shop floor but from a distant HQ, and no sense of quality or standards in its products. For something as serious as aircraft, I find this highly unconscionable. Thankfully Boeing seems to be finding religion amidst a series of massive f*ck ups. Time will tell.
The Man Who Killed Google Search (Where’s Your Ed At)
Similar to the above Boeing story, Google also fell prey to the suits coming in and f*cking up a perfectly good product.
It will be utterly hilarious if this experiment works, and other big companies follow suit. I’m not so secretly rooting for Bayer’s success.
Salesforce abandons pursuit of Informatica, source says (Reuters)
First, it was on; now, it’s off. Talking with data industry peeps, if you were an Informatica competitor, this would’ve been great for a couple of reasons. First, given Salesforce’s track record of zombifying companies it buys, Informatica would likely suffer the same fate. Second, a massive sale like that would boost the prospects for other data integration companies.
The AI hype bubble is deflating. Now comes the hard part (Washington Post)
I’ve got an article in the works talking about the upcoming AI hype cycle implosion. The big crux - lots of cool tools and demos, and so far, not a lot of people buying it (yet).
Other cool reads…
Benchmarking Report: Theseus Engine (Voltron Data)
Apple releases eight small AI language models aimed at on-device use (Ars
Technica)
The End of Agile – Part 3 (What Is Agile Really?) (TDAN)
FTC Announces Rule Banning Noncompetes (FTC)
Biden signs TikTok ‘ban’ bill into law, starting the clock for ByteDance to divest it (The Verge)
New Content, Events, and Upcoming Stuff
Monday Morning Data Chat
Coming up…
Yali Sassoon, and more…
In case you missed it…
David Yaffe & John Kutay - The State of Streaming and Change Data Capture (Spotify, YouTube)
Solomon Kahn - Customer-Facing Data Products, Why A/B Testing is a Waste of Time, and More (Spotify, YouTube)
Katharine Jarmul - Are We Solving the “Right” Problems with AI? (Spotify, YouTube)
Matt Turck - The 2024 MAD Landscape (Special Show) (YouTube)
Cedric Chin & Sam Taylor - Communicating Sophisticated Stuff to Stakeholders (Spotify, YouTube)
Martin Musiol - Martin Musiol - Generative AI: Navigating the Course to the AGI Future (Spotify, YouTube)
The Joe Reis Show
This week…
5 Minute Friday - Getting Buy-In (Spotify)
Vishnu Vasanth - Next Generation Analytical Query Engines (Spotify)
In case you missed it…
Kent Graziano - The Data(Ops) Warrior (Spotify)
5 Minute Friday - Data Oceans (Spotify)
Keith Belanger - The Art of Data Modeling (Spotify)
5 Minute Friday - Your Mileage WILL Vary With Analytical Data Modeling (Spotify)
Kishore Aradhya - Kishore Aradhya - Teaching Tech and Data in a FAST Moving World (Spotify)
Toby Mao - SQL Mesh, Simplifying Data Transformations, and more (Spotify)
Bill Inmon - History Lessons of the Data Industry. This is a real treat and a very rare conversation with the godfather himself (Spotify) - PINNED HERE.
Events I’m Speaking At
J On the Beach (Malaga, Spain) - May 6-10. Register here
GenAI Conference (London) - May 20-22 Register here
AI Quality Conference (San Francisco) - June 25th Register here. Rumor has it I’ll also be DJing there…
(Taking the Summer off, sort of…)
Big Data London - September 18-19. Register here
DataEngBytes (Australia) - Late September/Early October, TBA
Gitex (Dubai) - Fall, TBA
Helsinki Data Week - Fall TBA
Lots of other stuff in Europe - Fall, TBA
Asia - Fall, TBA
Thanks! If you want to help out…
Thanks for supporting my content. If you aren’t a subscriber, please consider subscribing to this Substack.
Would you like me to speak at your event? Submit a speaking request here.
Want to sponsor this newsletter? Fill out this short form.
You can also find me here:
Monday Morning Data Chat (YouTube / Spotify and wherever you get your podcasts). Matt Housely and I interview the top people in the field. Live and unscripted. Zero shilling tolerated.
My other show is The Joe Reis Show (Spotify and wherever you get your podcasts). I interview guests on it, and it’s unscripted and free of shilling.
Practical Data Modeling. Great discussions about data modeling with data practitioners. This is also where early drafts of my new data modeling book will be published.
Fundamentals of Data Engineering by Matt Housley and I, available at Amazon, O’Reilly, and wherever you get your books.
Be sure to leave a lovely review if you like the content.
Thanks!
Joe Reis