Alternative Data Weekly #151
September 15, 2023
Thanks for being here!
The Alterative Data Weekly is powered by Vertical Knowledge.
Announcement(s):
Let me know if you’ll be at the September 28th Neudata conference in San Francisco. I will be there.
We also have a team in London for the BattleFin Conference Sept 26-27 & Eagle Alpha Conference October 12. Let me know if you will be in London for both/either.
Theme that emerged in this week’s email is … Generative AI is driving important conversation about legal issues surrounding data ownership and lineage.
QUOTES
“Being data-driven today means incorporating data beyond your first-party data. It means enhancing and augmenting your internal analytics with even greater contextual data sourced externally.” – Jonathan Chin
News Articles
Podcasts
Cool Charts
Final Thoughts (drinking from a firehose)
#1 – Ben Ari published the transcript of an interview with Jonathan Chin Of Facteus On How To Use Data To Take Your Company To The Next Level. August 2023.
My Take: Really good read. There is a lot I could highlight, but will focus on the 5 ways a company can effectively leverage data to take it to the next level:
Upgrade your Information Sources
Looking Outside the Company’s Own Four Walls
Investing in Tools and Training to Empower Business Leaders with Data Analysis Skills
Treating Data Like a Product: Investing, Refining, Enhancing, and Growing with It
Being Open-Minded and Objective: Embracing the Unexpected Insights from Data
#2 – MIT Sloan published The legal issues presented by generative AI. August 2023.
My Take: We are very early in the use of AI. It is clear these models require a ton of data. Addressing questions about data ownership and lineage are hugely important. In line with the Center for Data Innovation article highlighted last week, industry leadership here is a must.
#3 – Wendy Turner-Williams published Data: The Intangible Tangible. August 2023.
My Take: Making raw data (intangible) into valuable insights (tangible). This is the goal. Wendy emphasizes the importance of, not just understanding the output, but the understanding the data journey (the source of data, the processing, potential biases, & how to use it efficiently).
BONUS: Magis’ AI Towns and Agent Based Modeling. August 2023. “What is particularly promising about this approach is that there exists the possibility we can simulate close-enough human behavior at the agent level and then recover population-level phenomena that we do not know about yet. This could revolutionize social sciences and economic forecasting because the cost of experimentation becomes very cheap and because experiments can easily be replayed in various configurations.”
What else I am reading:
Fast Company’s OpenAI addresses corporate data leakage jitters with ChatGPT Enterprise. August 2023.
Instacart’s The Next Era of Data at Instacart. August 2023.
Dave Hannibal of Seek published Why we are not (yet) doing generative AI. August 2023.
Jeremy Baksht’s The Price of Data in the Age of Prediction. August 2023.
Dylan Patel’s Amazon’s Cloud Crisis: How AWS Will Lose The Future Of Computing. March 2023.
Steve Cohen & Matthew Granade’s Models Will Run the World. August 2018 (h/t JB).
Source: Michael Watson’s Hedgineer podcast published an interview with Rich Brown How To Profitably Spend $100M on Data for Trading. May 2023.
My Take: This a great podcast series. The conversation covers a wide range of pertinent topics. Data rights, data ingestion, alt data, traditional data, AI uses cases, crypto, plus some 5-10 year predictions.
Most interesting to me was the conversation around use cases for alternative data. I am reminded how early we are in the process and how difficult it can be to put new data sources to work
Another interesting topic was the conversation around data rights. The data vendor has to make very clear that the rights are in place to the data buyers use case. This is getting more difficult as more data is created and monetized.
Highlights (48-minute run time):
Minute 01:20 – Rich’s background
Minute 05:00 – data granularity and mapping to KPIs
Minute 07:00 – buyside shops building automation to backtest (will sell-side adopt?)
Minute 09:00 – legal issues with data used to train LLM & AI models
Minute 12:00 – what about rights to derived products?
Minute 14:45 – when does a fund need to build out data team?
Minute 16:45 – thoughts on using data aggregators & the different types
Minute 17:45 – what about traditional data from a licensing perspective?
Minute 19:00 – how to know a data source I valuable & best practices
Minute 23:00 – looking ahead to next 5-10 years
Minute 26:00 – how to think about privacy at a global scale?
Minute 27:30 – discussion of data marketplaces
Minute 30:00 – how to think about all-in costs (beyond just data vendor license)
Minute 33:00 – how quickly can you get the data qualified / evaluated? AI use case here?
Minute 36:30 – finding data in data catalog (China example)
Minute 37:30 – do you use ChatGPT in your process?
Minute 42:00 – data providers are starting to connect the dots
Minute 43:30 – crypto thoughts … use cases for data (getting off-chain data on-chain is oppty … LINK is one my my personal favorites)
Minute 46:30 – Q: what are you working on now? A: Series of tools to get data in-house more quickly
Source: Center for Data Innovation’s Comparing Data Policy Priorities Around the World. September 2023.
I have seen & heard this topic come up more frequently. I thought this was a timely report.
I acknowledge this table can be tough to read…click on link to get better version. You will also see A LOT more detail about each country’s policies.
Drinking from a firehose.
New jobs & new roles can be overwhelming. There is a lot to learn and the importance of institutional knowledge is front & center.
There are two parts.
First is getting ingrained into the workplace. Getting everyone’s names, knowing who works with whom, understanding the culture … plus getting all the new tech down (Salesforce & MS Teams is new for me … feeling the need to become a power-user immediately, but that requires time).
The next is the product offering. Vertical Knowledge has a massive amount of uniquely valuable data. I am working to get my arms around all that we offer. Whoa!
The good news is there are a ton of resources and everyone is willing to pitch in to help, answer questions, and point me in the right direction.
Any time overwhelm kicks in, I remind myself to take time. Do one thing at a time. Get the basics down (how do I schedule a meeting again?). Make progress every day. It will click.
This is going to be a lot of fun!
Let me know if you’ll be in SF for the Neudata conference. I will be there.
We also have a team in London for the BattleFin Conference Sept 26-27 & Eagle Alpha Conference October 12. Let me know if you will be in London for both/either.
