Thanks for being here!
This is the Alternative Data Weekly for Friday, March 8, 2024.
Theme that emerged in this week’s email is … there is still too much friction in process of buying/selling data.
QUOTES
“Better data means better policies” - IMF Managing Director Kristalina Georgieva
News Articles
Podcasts
Cool Charts
Final Thoughts (Thanks)
#1 – Todd Harbour published Data as an Unacknowledged Commodity: The Case for a Formal Data Exchange. February 2024.
My Take: This is a very thorough article & worth reading for anyone paying attention to data marketplaces / exchanges (set aside some time, this is a detailed article).
I do not believe we have seen the working data marketplace/exchange model yet. Todd runs through the challenges and opportunities with examples, focusing on the difference between a marketplace & an exchange. Pitching the use of an exchange, Todd focuses on the benefits of strong regulatory structure, price discovery, standardization, while at the same time acknowledging the challenges of such a solution (privacy, IP control, etc).
#2 – Vin Vashishta’s Is Data Still A Competitive Advantage?. March 2024.
My Take: I’d recommend signing up for Vin’s writings if you are not already. In this article, I like his thoughts around data acquisition and data mobilization. Basically the difference between having data and using it. “The competitive advantage achieved from having access to a dataset is shorter than it used to be”. Said another way, “alpha” (HF speak for an advantage) used to be from accessing data that other did not or could not easily access. Now competing firms are better at using data, so even if you are the first to engage with a new dataset, the advantage will be short-lived.
#3 – Alex Boden’s Information Asymmetry. February 2024.
My Take: PE and VC firms are seen using data for deal sourcing and due diligence. Perhaps it is easy to monitor the identification of good deals, but tougher to measure the misses (didn’t invest in a bad deal). Will be fun to track over the years.
BONUS: Josipa Majic Predin published Venture Capital's New Era: AI's Journey From Enhancing Operational Efficiency To Alpha Generation. January 2024. “The gold rush for capturing the power of AI is already started and all mega funds are increasing their investments on data and data science teams.“
What else I am reading:
Adam Braff’s At the risk of repeating ourselves. February 2024.
Ethan Mollick’s Strategies for an Accelerating Future. February 2024.
Jason Saltzman’s Can GTM out hire it's data problem? February 2024.
Auren Hoffman’s Seconds to Strategy: How Your Relationship with Time Shapes Your Career. February 2024.
Tumblr and WordPress to Sell Users’ Data to Train AI Tools. February 2024.
Source: The Data Couch Podcast published an interview with Kashish Gupta, CEO of Hightouch. February 2024.
My Take: Good conversation around how data is used across organizations & how data teams worry about self-service, mostly due to QA concerns. That said, data is table stakes for most roles today & self-serve is seemingly the future. Data team should keep control of the data & the business teams get the tools to ask questions and get good (ie trustworthy) answer. The key is to have an iterative process & experimentation with good feedback loop.
Highlights (34-minute run time):
Minute 00:50 - intro to Hightouch
Minute 02:30 - make tools to use the data companies already had
Minute 04:00 - trying to put data in the hands of the people but the people don’t want it; data teams fear this will create chaos
Minute 07:00 - self-service is the holy grail; self-service defined
Minute 08:00 - Need to self-serve data from a place that is very organized
Minute 12:00 - core of Hightouch works is they are being data to existing SAAS tools (like Salesforce)
Minute 15:00 - email campaign example
Minute 17:00 - PetSmart example
Minute 19:30 - Hightouch description (customer segmentation)
Minute 22:00 - why does self-service fail at most companies. Data is hard. Self-service data is really hard.
Minute 25:00 - be clear on the “why” & drill down into the building blocks (quality, education, models, etc)
Minute 27:30 - AI and how incorporated into Hightouch
BONUS: Norges CEO Nicolai Tangen interviews LSEG CEO David Schwimmer. Thought minute 15 conversation around data & AI was particularly interesting.
BONUS 2: Erik Torenberg & Byrne Hobart’s The Riff podcast E16: The Fertility Crisis. ADW not necessarily suggesting a fertility podcast, but at minute 36 the conversations switches to data & AI interfaces. I thought this brief discussion was interesting.
Source: Ravit Jain posted Top 7 Data Terms Explained. March 2024.
𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞: A vast repository for raw, unstructured data.
𝐃𝐚𝐭𝐚 𝐌𝐚𝐫𝐭: A tailored subset of a Data Warehouse, focused on a specific domain.
𝐃𝐚𝐭𝐚 𝐌𝐞𝐬𝐡: A decentralized data architecture that empowers teams with ownership and control of their data.
𝐃𝐚𝐭𝐚 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞: A pathway that facilitates the seamless movement and processing of data.
𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞: A centralized repository for structured data, organized for efficient analysis.
𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲: The accuracy, consistency, and completeness of data, which is essential for trustworthy analytics.
𝐃𝐚𝐭𝐚 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲: The ability to understand and optimize the health of data systems, ensuring reliability, availability, and performance.
BTW ... check out The Ravit Show linked here.
BONUS: Exploding topics: Data Storytelling.
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