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Announcement(s):
I had a great week in NYC.
Theme that emerged in this week’s email is … AI and alt data are disrupting business as usual. Low-hanging fruit goes first.
QUOTES
“As the (alt data) space matures further, I believe we will see movement towards richer insights that offer even deeper understanding of what is happening in the world. Predicting top-line metrics will always have value, but leveraging alternative data to drive insight into nuanced metrics like customer composition, customer retention rates, lifetime value, and brand affinity excites me.” – Alex Schwartz of First Party
News Articles
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Final Thoughts (Quotes)
#1 – Kane Pepi published What is Alternative Data? Everything You Need to Know in 2023. July 2023.
My Take: This is a solid overview of the entire alternative data space. Covering the “what is alt data” basics, customer types, specific use cases, pros/cons, decision point considerations, etc. … this article should be on the must read list for those new to the space and even those who have been around a while.
#2 – Louise de Leyritz published How is AI Disrupting Data Governance?. July 2023
My Take: I’ve read lots about the impact AI will make on the data world. AI get a lot of attention & rightfully so. I like this article in particular because it takes a practical look at the changes happening now & those just on the horizon. Today it seems, at best, AI is supportive of existing procedures and is showing great potential to add significant value in the near future. For now, we still need a human-in-the-loop. Of most interest to me was the idea of a personal data assistant (similar to what Seek.ai is trying to solve). This tool basically allows non-data people to query structured data using natural language. This is here today. Perhaps the next step is to make this proactive … anticipate what questions you will want to ask.
#3 – Tom Sullivan published 6 types of alternative credit data for better loan decisions. January 2023.
My Take: This was a more detailed article than I’ve seen in the past about the topic of using alternative data to expand access to money. Bottom line, new lenders are taking alternative data sources into account when vetting loan applicants. Traditional FICO scores are just one input. Rental payment history, bill pay history, etc are considered. Experian estimates an additional 19M US adults could be properly evaluated with alternative data. Plaid is leading the way here. Big opportunity for those who can execute.
BONUS: Bo Brustkern of Fintech Nexus published How Lenders Are Driving Profitability Across The Loan Lifecycle with Alternative Data. July 2023. “Alternative data has allowed us to really be a friend alongside the complete journey. It’s also allowed us to improve our repayment rates,”
What else I am reading:
Patrick Chase & Jacob Effron published The Rapidly Decreasing Costs of AI and Why Databricks Bought Mosaic. June 2023.
Lenny’s Newsletter published How Snowflake builds product. July 2023.
Michael Fleder’s Forecasting with Alternative Data. December 2019.
Silicon Angle’s Connecting the dots on Snowflake’s Data Cloud ambitions. June 2023.
Bonus: SigTech interviewed Alex Schwartz of First Party. July 2023.
Bonus 2: Friend Jawad Mian of Macro Advisory firm Stray Reflections was interviewed by Barry Ritholtz on Masters in Business. July 2023.
Source: Mark Fleming-Williams interviews Mark Ainsworth, the former head of Data Science at Schroders. July 2023.
My Take: Echoing what I’ve noted in the past, it is good to hear the perspective of institutional investors actually putting data to work (both alternative & traditional). The conversation touches on productizing the data … first they understand what questions the business user is trying to answer (domain experience). The data team found the most success when they were most engaged with the investment teams and could discover what is worth doing before doing it. Validation before implementation. And it is better to find data that will add value across many teams, contributing tiles into the mosaic of decision making (easier to get budget too). Lastly, interesting end of podcast discussion about neurodiversity, specifically autism.
Highlights (70-minute run time):
Minute 01:00 – interview starts, Mark Ainsworth’s background
Minute 07:30 – Mark Ainsworth’s experience at Telefonica & intro to alternative data
Minute 14:00 – move to Schroeder’s; background & why it is interesting for Schroeder’s to get into Alt Data in 2014
Minute 21:00 – description of Schroeder’s team; getting started as 1st data person (25 people w/in 5 yrs)
Minute 30:00 – getting buy-in from the various investment teams; essentially competing w sell-side to answer questions
Minute 34:00 – did competition for alt data concern Schroeder’s?
Minute 38:00 – data’s advantage during the pandemic
Minute 43:00 – Mark’s opinion on the different banks data efforts (UBS, Morgan Stanley)
Minute 47:30 – what data did you find most useful? Answer “why” questions
Minute 55:00 – new technology platforms that allow investors to engage with data without an internal data team; pros & cons
Minute 58:30 – Mark’s interest in neurodiversity and its higher propensity amongst technologists
Minute 67:00 – what is next for Mark?
Source: Seattle Data Guy published Getting Unstuck In Your Data Career. July 2023.
Great article. And I like the visuals, so wanted to share.
This reminded me of the idea of talent stacking (I first came across this idea from Scott Adams, but upon googling it, there are quite a few people discussing this phenomena).
A visualization from another author on the benefits of talent stacking
Source: Tomas Pueyo’s How to Become the Best in the World at Something. September 2021.
A recurring theme in the articles I read about the data space is the importance of domain knowledge. If you can do the data work AND understand the business, you can add a lot of value.
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I’ve been thinking about the business of data a lot lately. In that process I came across a number of quotes that are worth sharing. Source (among others): Cornellius Yudha Wijaya.
“Data that is loved tends to survive.” -Kurt Bollacker
“If you torture the data long enough, it will confess.” — Ronald H. Coase
“The temptation to form premature theories upon insufficient data is the bane of our profession”. — Sherlock Holmes
“Every company has big data in its future, and every company will eventually be in the data business.” — Thomas Hayes Davenport
“Talented data scientists leverage data that everybody sees; visionary data scientists leverage data that nobody sees.” — Vincent Granville
“Data is not information, Information is not knowledge, Knowledge is not understanding, Understanding is not wisdom.” — Clifford Stoll
“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” — James Love Barksdale