Top Questions: Eagle Alpha New York Alternative Data Conference, 2025
Here's my preview and questions of Eagle Alpha's conference on February 12th, 2025
Eagle Alpha’s New York Alternative Data Conference includes a private equity track alongside the main conference data topics. This article previews the conference by sharing my questions for each speaker and panel.
https://www.eaglealpha.com/2024/05/12/alt-data-conference-february-2025/
There’s 3 key themes to the top questions on my mind
The Future of AI, Data Infrastructure, and Investment Technology
The Unique Challenges of Alternative Data in Private Markets
Sector-Specific and Niche Applications of Data
Welcome to the Data Score newsletter, composed by DataChorus LLC. The newsletter is your source for insights into the world of data-driven decision-making. Whether you're an insight seeker, a unique data company, a software-as-a-service provider, or an investor, this newsletter is for you. I'm Jason DeRise, a seasoned expert in the field of data-driven insights. As one of the first 10 members of UBS Evidence Lab, I was at the forefront of pioneering new ways to generate actionable insights from alternative data. Before that, I successfully built a sell-side equity research franchise based on proprietary data and non-consensus insights. After moving on from UBS Evidence Lab, I’ve remained active in the intersection of data, technology, and financial insights. Through my extensive experience as a purchaser, user, and creator of data, I have gained a unique perspective, which I am sharing through the newsletter.
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Eagle Alpha New York Alternative Data Conference Agenda: Wednesday, February 12th, 2025
Main Track, Morning
Welcome & Opening Statements
Michael Finnegan, CEO of Eagle Alpha
8:50AM - 9:00AM
MAIN ROOM
Join us for the official kickoff of the Eagle Alpha Alternative Data Conference with a welcome & opening remarks led by CEO Michael Finnegan.
Question: What key factors will drive the evolution of the alternative data industry in 2025? Will 2024’s trends accelerate, plateau, or shift?
Engineering Tomorrow’s Hedge Fund Technology: Avoiding Data Infrastructure Lock-in and Deploying Useful AI Applications
Michael Watson, Hedgineer in conversation with Thomas Combes, Eagle Alpha
9:00AM - 9:30AM
MAIN ROOM
Join us for a discussion with Michael Watson, founder of Hedgineer on the future of hedge fund technology. We’ll explore how open table formats1 and hybrid compute engines2 can prevent data infrastructure lock-in3 and delve into real-world applications of AI that are transforming how hedge funds operate.
Question: It seems like each week there is a new generative AI4 model available with either better reasoning performance or is more cost-effective. What parts of the data and tech stack should remain flexible to accommodate evolving AI models, and what should be stable for long-term reliability?
New to Market & Fresh Features – Vendor Presentations
An exciting session where we’ll dive into the latest advancements and features from top data vendors.
9:30AM - 10:30AM
MAIN ROOM
Question: For the new vendors, keep these questions in mind while presenting—How does your data solve real investment questions? What sets your methodology apart from competitors? How do you ensure compliance and trust? Good luck with the presentations.
Private Equity Track, 9:15am- 12:30pm
Private Equity Track – How Investors and Lenders in Private Companies are Using Technology & Analytics as a Competitive Weapon
David Teten, Versatile VC
9:15AM - 9:45AM
BREAKOUT ROOM
Explore the current state of alternative data adoption in the PE/VC industry with practitioners who are actively using these data sources. This session will provide a firsthand look at how firms are integrating alternative data into their investment strategies.
Question: Where are leading asset managers seeing the biggest impact from data and analytics—deal origination, due diligence, operations, portfolio insights, or elsewhere?
Private Equity Track – The Fund of the Future: Embracing Technology and Data in Private Equity
Trevor Ross, West Monroe
9:45AM - 10:00AM
BREAKOUT ROOM
Explore how private equity firms can leverage technology, data analytics, and innovation to gain a competitive edge. West Monroe will break down the “Fund of the Future” framework, offering strategies to drive growth, efficiency, and value creation in today’s evolving market.
Question: How does the ideal data and tech stack differ between large private market and public market asset managers? What are the shared and distinct infrastructure requirements?
Private Equity Track – Alternative Data and Private Equity – Use Cases and Applications
With G2, Dodge Construction Data and Clootrack, moderated by Brendan Furlong, Eagle Alpha
10:00AM - 10:30AM
BREAKOUT ROOM
Join leading data vendors for a panel discussion on how alternative data is transforming the private equity landscape, with a focus on real-world applications and actionable strategies.
Question: Given the lack of continuous feedback loops in private markets, short decision time frames, and limited data tagging, how should data providers and asset managers rethink their approach to alternative data? Some context behind the question: unlike private markets, public markets offer a continuous feedback loop where consistently processed data insights scale the decision-making process. There is a short window for making a private equity investment decision instead of the ongoing decision-making process in public markets. The underlying data is not likely well tagged related to the private companies compared to the much better tagging of data to tickers in public markets.
Private Equity Track – Fireside Chat: Value Creation Themes: Talent, Revenue, Operations
With Tom Liu, Managing Partner / Founder of Ideate Capital, in conversation with Conor Taggart, Eagle Alpha
12:00PM - 12:30PM
BREAKOUT ROOM
Join us for a fireside chat with a former Head of Data at a top private equity firm as we dive into the cutting edge of value creation. We’ll explore how top firms are securing elite talent, leveraging enriched data to drive higher close rates, and harnessing LLMs5 to optimize every stage of the deal cycle—from sourcing to contract execution.
Question: What advice would you give PE firms to foster strong collaboration between investors and data teams as new data and technology capabilities are applied to PE investments? How can data companies better support the data teams at PE asset managers?
Main Track, Afternoon
Consumer Insights and Product Developments from Leading Vendors
Brian Callahan, Facteus, Thomas Grant, Apptopia and Charm.io, moderated by Brendan Furlong, Eagle Alpha
12:00PM - 12:30PM
MAIN ROOM
Gain valuable insights into consumer behavior and witness the latest product innovations as a panel of leading vendors share their expertise. This interactive session will explore the intersection of consumer needs and cutting-edge product development.
Question: How have recent trends in premium and luxury consumer brands differed from 2024? How does this compare to mass-market and value-focused brands?
The Opportunities And Nuances of Deploying Unstructured Data In Quant Trading Models
Professor Francesco Fabozzi, Yale University; Didier Lopez, OpenBB; and Dan Joldzic, Alexandria Technology; moderated by Christos Koutsoyannis, Atlas Ridge Capital.
1:15PM - 2:00PM
MAIN ROOM
Join leading practitioners for a discussion on the practical applications of unstructured data in quant6 trading. This session will address the opportunities and nuances of deploying these models, including data sourcing, processing, and integration.
Question: One aspect of leveraging unstructured data in systematic investing7 is extracting sentiment as a signal from news sources. However, some news is recapping a previously known impact on share prices, while others are providing new information that would affect share prices. Have systematic funds successfully built scalable causal AI models8 that identify true new signals versus priced-in insights, or is this still an experimental stage?
2025 Compliance: What to Expect from the New Administration
Sergio Pagliery, Schulte Roth & Zabel and Emilie Abate, Iron Road Partners, moderated by Ciaran Ryan, Eagle Alpha
3:30PM - 4:00PM
MAIN ROOM
Question: There is a general narrative of deregulation in the current US government. If US regulations and oversight are relaxed for alternative data providers and asset managers who use alt data, will the industry be able to self-police effectively to ensure the long-term viability of the industry?
Alien Intelligence, Myth and Reality
Frederic Siboulet, consultant (former Deloitte, EY & IBM)
4:00PM - 4:30PM
MAIN ROOM
Over the past three years, there has been a rapid acceleration in the role of artificial intelligence, particularly with GPTs and LLMs. We examine why, how, and where AI may be augmenting human performance in quantitative and operational tasks. We also consider how this new paradigm relates to model structures and data utilization, both during training and inference. In addition, we discuss the relationship between model size and model risk, and explore the potential evolution of data science given the new agentic frameworks9 available to businesses.
Question: Which asset managers or data firms are seeing the most value from agentic AI frameworks, and which use cases have made it to production? Clever presentation title!
Uncorking Alpha: Data-Driven Strategies in Fine Wine Investing
Tommy Jensen, Wine Capital Fund in conversation with Ciaran Ryan, Eagle Alpha
4:30PM - 5:00PM
MAIN ROOM
Data driven wine investing? Yes please. Join Tommy Nordam Jensen (CEO, Wine Capital) and Ciaran Ryan as they discuss Selection, Storage and Selling of tier 1 investment grade wines.
Questions: Fun topic to end the day. I think I might have all the questions—but here’s a few! What measurable weather patterns produce top-rated wines by region, and which recent vintages benefited those conditions? Can the Normalized Difference Vegetation Index (NDVI)10 and other satellite-derived data predict vintage quality? How can data identify oversupply risks that impact investment returns (good for consumers, bad for investors)? Which wine marketing gimmicks fail to add investment value (e.g., aging wine under water as if it were discovered after being lost at sea)? And most importantly—will there be samples?
What questions do you have for the panelists? Leave a comment below
Would this content help someone attending or presenting at the conference? Feel free to forward it on.
- Jason DeRise, CFA
Another reoccurring theme about data conference agendas is that they love jargon. A lot to define below (ok, to be fair, I added some jargon in my questions too). A bunch of new jargon terms to add to the Jargonator:
Open Table Format (OTF): an open-source system for storing and managing large amounts of data. OTFs are built on top of existing file formats, like Parquet and ORC, and provide a layer of abstraction on top of data lakes.
Hybrid Compute Engines: Systems that allow data processing to occur across multiple computing environments (on-premises, cloud, and edge computing) to optimize performance, cost, and scalability.
Infrastructure Lock-in: A scenario where firms become dependent on a particular technology, cloud provider, or data format, making it costly or difficult to switch to alternative solutions.
Generative AI: AI models that can generate data like text, images, etc. For example, a generative AI model can write an article, paint a picture, or even compose music.
Large Language Models (LLMs): These are machine learning models trained on a large volume of text data. LLMs, such as GPT-4 or ChatGPT, are designed to understand context, generate human-like text, and respond to prompts based on the input they're given. It is designed to simulate human-like conversation and can be used in a range of applications, from drafting emails to writing Python code and more. It analyzes the input it receives and then generates an appropriate response, all based on the vast amount of text data it was trained on.
Quant funds: Short for "quantitative funds," also referred to as systematic Funds. Systematic refers to a quantitative (quant) approach to portfolio allocation based on advanced statistical models and machine learning (with varying degrees of human involvement “in the loop” or “on the loop” managing the programmatic decision-making).
Systematic Fund: Systematic refers to a quantitative (quant) approach to portfolio allocation based on advanced statistical models and machine learning (with varying degrees of human involvement “in the loop” or “on the loop” managing the programmatic decision-making).
Causal Analysis/Causal AI: A method of identifying relationships that suggest causation rather than mere correlation in statistical data, focusing on determining what affects an outcome.
Agentic AI Frameworks: A type of AI system that autonomously makes decisions and executes tasks with minimal human intervention, often used in data-driven workflows to enhance efficiency and automation. An example could be a large language model chat model used as an interface that calls other AI models depending on the prompt and, in turn, leverages other specific AI agents that handle specific tasks to enable the outcome.
Normalized Difference Vegetation Index (NDVI): a metric derived from satellite imagery that measures vegetation health by comparing the near-infrared and red light reflected by plants. Values range from -1 (non-vegetation) to +1 (healthy vegetation).