Alternative Data Weekly #234
April 18, 2025
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The theme that emerged in this week’s email is … Big acquisition in the space… more scale = accelerated growth?
QUOTES
“AI is definitely changing the alternative data landscape towards more automation and processed signals. Information is every fund's competitive edge and has been limited by the capacity of their data scientist. This is changing now as data and research teams can do a lot more with a lot less by using LLMs across the entire data stack.” – Adrian Krebs, Kadoa
News Articles
Podcasts
Cool Charts
Final Thoughts (Frozen Four)
#1 – Abraham Thomas published Data and Defensibility. April 2025.
My Take: Bookmark this one. Where to begin? There is too much good stuff to try to summarize, so I’ll just share what resonated with me.
I’m curious about the disruption of the SoR (system of record) model. Does AI create workflows that live outside the SoR where data inputs and outputs are done via some sort of AI workflow rather than logging into the various systems? Today, workflows involve accessing data in disparate systems (CRM, O365 tools, Bloomberg, Workspace/Eikon, etc) … how does this change & will this changing workflow disrupt the SoR model?
Moats (similar recent article from Matt Ober)
“This essay is for founders, investors, and operators who care about data moats: who want to build them for their own companies, or compete with rivals who have moats of their own. But as we’ve seen, “data moats” are a wide and varied concept.”
#2– Jason Derise published There's No Such Thing as a "Data Buyer". April 2025.
My Take: Note there is a paywall for this article (worth it). Jason shares five personas who are involved in the buy/don’t buy decision making process. Knowing which type of persona you are dealing with will help you modify your pitch accordingly.
#3 – Adrian Krebs published AI, Automation, and Alpha: Alternative Data Trends 2025. April 2025.
Take: AI is changing the landscape. I am watching where value flows. Is it to the data owner? Is it to the person monitoring the data for quality issues? Is it to the person generating the insight? Early on, I think it flows to the AI systems that solve specific problems and automate tasks that used to take days (now done in minutes). In the future, it will be the new workflows that are created with AI supplanting rote activities and freeing decision makers to apply creativity, judgement, and human empathy.
BONUS: Auren Hoffman published Vendor Management is the MOST Important Skill. April 2025. “revenue per employee will go up 3-10 times in the next decade … because half your ‘employees’ are just Chrome tabs and Zapier zaps now.”
What else am I reading:
Jack Salva published AI Starts With Data: How to Build a Future-Proof Foundation for AI Readiness. April 2025.
NewCo alert: Alternata
Jon Jacobson published The Ethics Of Consumer Data: Avoiding Pitfalls And Building Trust. April 2025.
Bill Ronkoski published The Power of Data Partnerships. April 2025.
Dan Entrup published an Interview with Big Data Federation. April 2025.
Sanjeev Mohan published To MCP or Not to MCP Part 1: A Critical Analysis of Anthropic’s Model Context Protocol. April 2025.
Eugenio Caterino published The Datarade Pulse: News & Insights from the Data & AI World | March 2025. March 2025
Duncan Gilchrist & Jeremy Hermann published The End of Programming as We Know It. March 2025.
Jack Derwin published The rise of ‘alt-data’ — fundies’ secret weapon in the quest for alpha. February 2025.
Source: Boardy’s Only the Paranoid Survive in the Age of AI: Boardy's Take on Andy Grove's Classic. April 2025.
My Take: In a first for me, I listened to a podcast with the audio being only a bot. Nots sure if any humans had a hand in writing the blog, but the blog was read by a bot (Boardy). The audio was very obviously a bot, but a pretty good listening experience considering that fact.
I like the idea of using AI to watch for key inflection points, industry competitive signals, market shifts, tech breakthroughs. This is in line with what ModuleQ … we only surface (“pushed” via unpromoted alerts) the most relevant information based on the context of your persona and workflows.
There is a changing division of labor between humans and AI. Stay in front of this. The saying is that “AI won’t take you job, but rather a human using AI will take your job” . Determine what AI is good at (scanning news, processing lots of data, repetitive tasks, etc) and “outsource” that to that system and focus on the stuff humans do better (i.e. judgement, empathy, relationships, etc).
"Our AI systems continuously monitor competitive threats, regulatory changes, and technological disruptions, but this doesn't make us defensive. Instead, it frees our human creativity to focus on generating new opportunities. The paradox is that by delegating paranoia to AI, we've become more innovative rather than more cautious.” (27:00)
Highlights (36-minute run time)
Minute 02:00 – “productive paranoia”
Minute 03:30 – “personal awareness stack”; only high relevance alerts
Minute 04:20 – thinking about the workflows of your business
Minute 07:00 – Develop your "response muscles" rather than just your "awareness muscles."
Minute 08:30 – constant environment scanning is exhausting, particiularly with so much environment to scan
Minute 11:00 – "Is this thought leading to a specific action I can take today?"
Minute 13:00 – Competitor Analysis vs Ecosystem Awareness
Minute 16:00 – division of labor between AI & humans
Minute 20:00 – “distributed vigilance” … network function
Minute 27:00 – AI systems continuously monitor competitive threats, regulatory changes, and technological disruptions
Minute 29:00 – threat intelligence/opportunity intelligence
Source: Abraham Thomas published Data and Defensibility. April 2025.
Frozen Four.
I had a chance to attend the Frozen Four in St Louis last weekend. My alma mater Penn State made the tourney for the first time. It was quite an event.
Penn State made the jump to NCAA Division 1 status in 2012-13. A major gift from the Pegula family, funding a new rink and scholarships, helped make it all happen. The team has been consistently competitive in the tough Big Ten conference, and this year broke through, getting hot in the second half of the year.
I played at PSU ‘91-’95 when it was a club program. We were a very competititive D3 level team, skill-wise, a perfect fit for me. Participating in a sport made a big school much more manageable, allowed me to lead, stay physically active, play a sport I loved (and continue to love), and develop some lifelong friendships. I’ve continued to stay involved with PSU hockey as an active alum, supporting however I am able, showing up at events, and being an active member of the community.
Being there in StL with friends was a wonderful experience, capping 40+ years of hard work from a ton of people. It has been fun to be a part of the ride.
“I like the idea of using AI to watch for key inflection points, industry competitive signals, market shifts, tech breakthroughs.” I agree. It’s works, not in the lab, but in the real world. All my best, Drew.