🎯 Mark Freeman II

onthemarkdata.com | Senior data engineer helping brands with GTM and content strategy.

I'm a community health advocate turned data engineer interested in the intersection of social impact, business, and technology. My life’s mission is to improve the well-being of as many people as possible through data—especially among those marginalized.
 
As the founder of On the Mark Data, I use this platform to help brands connect to data professionals through captivating content.
 
I received my M.S. from the Stanford School of Medicine and I'm also certified in Entrepreneurship and Innovation from the Stanford Graduate School of Business. In addition, I have worked within numerous startups where I have put machine learning models into production, integrated data analytics into products, and led migrations to improve data infrastructure.
 
The culmination of my technical skills, content success, and experience within startups would make me an asset whether you are looking to create a successful content strategy, engage in influencer marketing campaigns, or develop a go-to-market strategy for your startup.

You can learn more about opportunities to collaborate, my media appearances, or my content at onthemarkdata.com.

Tech Lead, GTM Engineering

• Joined as employee one to lead GTM at Gable to help us reach our first customers.
• Worked with the CEO to establish our GTM strategy, content strategy, and messaging for technical audiences.
• Building internal data products to drive our GTM strategy and sales.

Hannes Mühleisen (co-founder of DuckDB) doing his slides like SQL queries is so damn cool.

The most powerful communication is often what's not said.

Dev 🤝🏼 GTM | O’Reilly Author | [in]structor (33k+ Learners)

No alternative text description for this image

Joe Reis recently inspired me to consider Claude Code as a writing tool when he challenged the notion of context graphs.

He essentially took the Foundation Capital article that has been going viral and ran it through Claude Code.

It instantly transformed a very theoretical article into an entire code repo you could explore on his public GitHub (then used that as a tool to critique).

A thought then popped into my head:

"What if my writing was so clear that you could throw an entire article into Claude Code and it would one shot a working POC of the presented ideas."

Welp, the implementation chapter of our book (Ch. 7) is public on GitHub and is stored as a README file.

So let's see if my writing is clear enough for AI to one shot it.

I downloaded the repo to my local machine, got rid of every file except the README, the JSON dataset, and a folder of diagrams from the chapter.

Then I prompted: "This is my technical chapter of the book. Implement it."

I couldn't believe it... In about 10 minutes it was spinning up a Docker image, loading data into Postgres, and then running my tests.

Keep in mind I spent a couple intense weeks building that codebase for the book.

To be clear, I'm not advocating for such code to be useable, but rather it's now a tool that I can use to further validate my writing.

Present your novel ideas.
But show the working POC.

It's the same as in academia where you have research papers that include code and data for repeatability.

The bar has risen for everyone now. Talk is cheap.

Crazy Idea: I use claude code on a live stream where I'm building an app from scratch.

But...

People on the live stream can enter prompts on my behalf while I'm building to either help or mess with the project.

I think the chaos would be both fun and hilarious.

You didn't hear it from me, but the coolest talk at Data Day Texas is happening at 2:55PM in room 204 👀

Live coding exercise for my conference talk at Data Day Texas? You bet!

Saturday - 2nd Floor - Ballroom 204

Code: The Untapped Metadata Source Driving Most Data Failures

Over the past three years, collaborating with organizations implementing data contracts and writing the O'Reilly book on the topic, it has become abundantly clear that data is surprisingly the wrong surface to address systemic data issues —we actually need to focus on code. Code not only defines what data is captured and moved through software systems, but it's also the ultimate source of truth in how a business operates and its documented changes over time. This is evident in how some of the most significant internet outages can be traced not only to code changes, but also to how those changes affected underlying data models. In this talk, I share case studies and lessons learned in extracting metadata from code and using it to enforce expectations across software systems and data products.

Remember back in the ancient internet times when you could use this cool thing called HTML to customize your Myspace profile.

Just randomly hacking away at sections to see what changed. Copy and pasting random code and hoping it works.

Vibe coding feels eerily similar.

What data scientist experienced in 2023 with the realease of ChatGPT is the same experience software engineers are experiencing today with Claude Code.

Back in 2022 I was transitioning from data science to data engineering, and a major project that led to that promotion was building and deploying a natural language processing pipeline.

Back then I was using SpaCy, which was an opinionated framework for implementing the latest production-ready NLP models.

Yeah... I open up ChatGPT and immediately see the "advanced" work I put into production was now antiquated.

While I wouldn't throw an LLM at my production project back in 2023, I was intimately aware of what was required to get business value out of text.

What ChatGPT showed me was that a large portion of the difficult parts of NLP were now just a simple API call... and more importantly, highlighted the inflection point if the momentum of change followed.

Fast forward to today, and so many software engineers built side projects over the holiday break and experienced the exact realization I had back in 2023.

"This LLM accomplished way more than I expected, and I can see an inflection point if this trend continues."

Imagine what will be accomplished in the next few years.

Joe Reis 🤓

Chief Operating Officer

Best-Selling Author | Data Engineer and Architect | Recovering Data Scientist ™ | Global Keynote Speaker | Professor | Podcaster & Content Creator

I write. I build. And I’m working on something new for the data community.More soon. ✍️📚⚡️

Ternary Data are veteran data engineers and “recovering data scientists” who have firsthand experience with the challenges of succeeding with data. We offer practical data engineering advice.

If you're at Data Day Texas on Sunday morning, Bill Inmon and I are hosting a very rare "Ask Bill anything." 

Be there and chat with the Godfather himself.

Joe Reis

Are BI dashboards going the way of the dinosaurs? 🦕 🦖📉

Barry McCardel and I recently met up at the Hex office for a great chat about the future of BI, AI agents in analytics, and much more.

Links to YouTube and podcast in the comments.

Always great to catch up with Gavin Hupp. 

He's a down-to-earth and awesome leader in the data industry. Give him a follow.

Is self-serve BI a myth? As Barry McCardel says, this seems like a nirvana customers have been promised for decades, but never quite seems to materialize.

Barry and I recently had a chat in the Hex office to discuss the future of BI, AI Agents, and much, much more.

Watch on YouTube: https://lnkd.in/g2iAGZKh

“Sadly, many people in our industry equate selling with playing the status game of one-upping each other and looking smarter than the other person. These people insist on talking above their buyer’s heads, then wonder why the buyer isn’t buying. Complicated things seem “cooler” than something simpler. As Warren Buffett said, “You don’t get any extra points for the fact that something’s very hard to do.””

Also, don’t be Uncle Rico.

Read more:

Open article: Uncle Rico and the Tragedy of the Great Idea That Goes Nowhere by open.substack.com

Uncle Rico and the Tragedy of the Great Idea That Goes Nowhere

Is the AI hype bubble about to be cooked? 

Prolific author and all around legend, Cory Doctorow, and I had a chat about this, enshitification, and much more. Enjoy!

Links in the comments.

1982. Megatrends talked about the end of the industrial base toward knowledge. That happened.

Replace past nouns with present nouns, and who knows what comes next, but it’s eerie…

Principal Architect @ Posit, Chief Scientist @ Voltron Data, GP @ Composed Ventures

And now there were 14. Welcoming Joe Reis to Spicy Takes!

https://lnkd.in/ehyXJRKS

Open article: Joe Reis by joereis.spicytakes.org

taplio

The Battle

🎯 Mark Freeman II

Joe Reis 🤓

Followers

Posts

Engagements

Likes

Performance Score🎯 Mark Freeman II's LinkedIn Performance

Performance ScoreJoe Reis 🤓's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

🎯 Mark Freeman II

Joe Reis 🤓

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}🎯 Mark Freeman II's LinkedIn Performance

Performance ScoreJoe Reis 🤓's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance Score🎯 Mark Freeman II's LinkedIn Performance