Alternative Data Weekly #214

November 29, 2024

Nov 29, 2024

Thanks for being here!

The theme that emerged in this week’s email is … the importance of starting with the big-picture strategy before digging into the data.

QUOTES

“Consistent value creation with data is already a decisive competitive advantage for companies today, and in the near future it will even be essential for survival.” – Jens Linden

"…grocery shopping habits can serve as a reliable indicator of financial responsibility and loan repayment capabilities.” – Jon Jacobson of Omnisient

News Articles
Podcasts
Cool Charts
Final Thoughts (Thanksgiving)

#1 – Jens Linden published The Root Cause of Why Organizations Fail With Data & AI. November 2024.

My Take: Article of the week! The bottom line is to start with the business strategy. The author points out that most companies (in his market) do not have a clear business strategy in place from which you can derive data needs. I like the author’s notion that the most successful companies in the future will be those that realize data is a strategic asset rather than an operational byproduct.
Part 1 of this series: The Data Strategy Choice Cascade. September 2024.

#2 – Jon Jacobson of Omnisient published Why Grocery Data Is A Gold Mine For Digital Marketers In Financial Services. November 2024.

My Take: Omnisient is pursuing use cases for grocery data, including improving financial institution marketing effectiveness & determining consumer creditworthiness. Using “data for good” should include expanding access to credit. (See related article from September: How Shopping Habits Can Reveal Credit Risk To Banks And Insurers).

#3 - Barr Moses & Tomasz Tunguz published Top 10 Data Engineering & AI Trends for 2025. November 2024.

My Take: I’m a sucker for a good Top Ten list. There are a lot of thought-provoking ideas here. I’ll focus on #10 Agentic AI. While there is a lot of promise here, broad adoption is yet to be achieved (and frankly seems quite a long way off). That said, we at ModuleQ have an #unpromptedAI offering, where the AI understands your workflow and delivers to you the right information at the right time. This removes the risks associated with generative AI & effectively addresses the information overload problem we all face.

What else I am reading:

Code Willing Webinar Tuesday, December 3: From Data to Trade

Sven Balnojan published The head of data's first priority. November 2024.

G20 Data Gaps Initiative (an interesting initiative that not many people seem to know about)

Finimize published Goldman Sachs Taps Alternative Data To Predict Retail Trends. November 2024.

Julien Lafaye, Joel Farvault, and Matthieu Bonville published How CFM built a well-governed and scalable data-engineering platform using Amazon EMR for financial features generation. November 2024.

Nicholas P. Brown and Carolina Mandl published Investors mining new data to predict retailers' results. November 2024.

Ethan Mollick’s Getting started with AI: Good enough prompting. November 2024.

Nick Zervoudis published Launching my first course on Data & AI Product Management. November 2024.

Jason Derise published Closer to Fine: The Paradox of Invisible Success. November 2024.

Scott Hall’s Data Providers.How to maximize revenue. Part 2. November 2024.

Bradley Saacks published This trade secrets lawsuit has the alternative data industry buzzing. November 2024.

Source: Marc Greenberg of The Long and The Short of It Podcast, published episode 3: My Favorite Nerds on Data and AI. He is joined by Qaisar Hasan, CEO and founder of Maiden Century, and Adam Braff, founder of Braff & Company.

My Take: I enjoyed this interview with two people I’ve gotten to know over the years and admire. It is interesting to hear how they got where they are (origin stories), and what they are building today.
Alpha decay is a real thing. It is getting harder to generate alpha from alternative data (perhaps it is less “alternative”?). This is partially a result of everyone realizing there is alpha to be had, but also the fact that the tools available are getting better.
What advice do you have for young people getting involved (question asked of the interviewees)? First, pick an area/sector where you will dive deep and establish your genuine interest. Second, understand that all human beings carry biases with them … be aware of that and be open to new things/ideas...looking for data to support your thesis. Understand the bias in the data and be objective about your analysis.

Highlights (58-minute run time):

Minute 02:30 – intro for Qaisar & his background, and Maiden Century’s background.
Minute 07:00 – intro for Adam & his background.
Minute 09:45 – who are the influences for both Adam & Qaisar.
Minute 17:30 – alpha decay in recent years (now a cost of doing business, table stakes).
Minute 23:30 – what advice do you have for people to best use the tools currently available?
Minute 32:30 – data and the recent election. Polling errors.
Minute 38:00 – NFLX test case.
Minute 42:00 – will prediction markets be incorporated into platforms?
Minute 44:00 – advice for people using data in investing
Minute 48:00 – if you were research director how would you think about new data sources?
Minute 51:00 – what kind of data should I bring in to help me?
Minute 52:45 – how to think about return hurdles?
Minute 55:45 – what are the people doing this “well” doing that others are not?

#1 – Jens Linden published The Root Cause of Why Organizations Fail With Data & AI. November 2024.

My Take: Article of the week! The bottom line, start with the business strategy. The author points out that most companies (in his market) do not have a clear business strategy in place from which you can derive data needs. I like the author’s notion that the most successful companies in the future will be those that realize data is a strategic asset rather than an operational byproduct.
Part 1 of this series: The Data Strategy Choice Cascade. September 2024.