🎯 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)

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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.

Debbie Botha

Member of the D^3 Institute Industry Council at Harvard Business School, Dalebrook Media Middle East Managing Director

I have directly managed data and AI teams form small 3 person teams to large 30+ person teams throughout my career.  As a consultant, I managed more than 10 large and complex data, analytics and AI projects from strategy to successful implementation, including assembling multinational teams of experts to ensure success.  As manager in Industry Organizations, I managed 3 large data and AI teams to successfully foster data value driven organizations.  I leverage my deep understanding of the successes and challenges of Data, Analytics and AI Leaders to help elevate the impact of these Leaders in Industry Organizations and help them grow in their careers.  

 I am passionate about producing small and intimate to large and complex events from agenda, speakers, audience,  partners, sponsors, logistics, and promotions to execution.  In the last 2 years I have produced  12 intimate executive luxury experiences, 5 large and complex events and  7 virtual events.

I have extensive experience in giving coaching to executives, large corporate audiences and architects.  I use design thinking and experiential learning techniques and love engaging the audience.  I hold workshops with C-suite executives to develop a Data and AI Strategy to execute the Business Strategy.   I hold roundtables to facilitate executives, and relevant stakeholders discuss hot topics, challenges and successes to help them learn from each other. 

I help others grow in their careers by mentoring, teaching and speaking at Events, and developing communities like Women in AI with 40K members in 150 Countries.  On the Board of Directors I formed a team of 20 executives, driving partnerships for WAI across the globe.  I inspire, educate and connect my community of 130+ CDAOs in the Middle East.

I am a Digital, Data and AI Coach on being data and AI value driven in a very practical way.  I help companies develop and implement Chief Data, Analytics & AI Offices with Data and AI Strategies, operating models, teams and Architectures.  I help Organizations to implement Data and AI Literacy programs across the organization.

While at IBM (2013 to 2021), I had several leadership roles.  I was an Executive Information Architect, a Client Technical Lead in UAE, was in the Worldwide Client Engagement Team reporting to the Global Analytics CTO and before that a Senior Managing Consultant in South Africa.

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🎯 Mark Freeman II

Debbie Botha

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The Battle

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Debbie Botha

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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

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