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In addition to our raw data collections, Babel Street | Vertical Knowledge is launching a growing number of research-ready refined products … self-storage, real estate, locational whitespace, footwear, handbags, and many others … please reach out to learn more.
Theme that emerged in this week’s email is … Data is tough to “get right” but pays off when you do.
QUOTES
“It’s an exciting time to be in data and AI.” Brad Schneider, Edge of AI podcast
News Articles
Podcasts
Cool Charts
Final Thoughts (Research Ready)
#1 – Maiden Century’s Qaisar Hasan published The (Ugly) Truth About Backtests. January 2024. (related white paper).
My Take: Backtesting is a key issue that extends the data sales cycle. This article touches on all the hot-button issues. I like Qaisar’s idea that in addition to the math, you need to add some human & business intuition to the process…easier said than done!
#2 – Seattle Data Guy Published 7 Habits Of Effective Data Managers. January 2024.
My Take: If you are in the data space you need to be following Seattle Data Guy. Great content.
Here are the 7:
The Ability To Prioritize and Say No
Collaboration
Clear Process of Deploying Results
Team Empowerment
Trust Builders
Deep Domains / Business
Investing in the Development & Growth of their Team Members
#3 – IBT published How Analyzing Publicly Available Information Can Help Businesses. January 2024.
My Take: My VK colleague Rayne Gaisford authored this article. PAI (Publicly Available Information) is powerful when collected at scale, organized, and delivered in a timely fashion. In the article Rayne runs through several use cases demonstrating how decision-makers of all stripes can benefit from better information.
A key element overlaying this entire process is the ethical collection of information and adhering to legal & ethical requirements.
BONUS: Court Rules Meta's Terms Do Not Prohibit Scraping of Public Data. January 2024. “It means that the court has ruled that Bright Data did not violate Meta’s terms of service or breach any contract with Meta by scraping public Facebook and Instagram data. As a result, the court dismissed Meta’s breach of contract claims against Bright Data.” Click here for related post/thoughts from Hope Skibitsky.
What else I am reading:
WSJ’s Meet the Investors Trying Quantitative Trading at Home. January 2024.
Michael Rhodes published Part 1: Revolutionizing the Onboarding Journey for Data Providers and Consumers. January 2024.
The Web Scraping Club published How scraping a single website costed thousands of dollars in proxy. January 2024.
BusinessWire published Babel Street Announces Strategic Acquisition of Vertical Knowledge, Bolstering Leadership in Identity Intelligence and Risk Operations
Source: Edge of AI podcast interviewed Brad Schneider of NOMAD Data. January 2024.
My Take: Brad has been in this space for a long time and is worth watching. NOMAD goes a long way towards solving the data discovery problem. They created an NLP powered data search engine addressing the affliction of too much information & how to sort through it. Superior to traditional “data yellowpages”
AI is all about data. LLMs are powered by textual data & not just external data, but also internal data which today is underutilized.
Financial & advertising data is most mature. Everything else is open field running opportunity. Consultants, telcos, retailers … are the early adopters
Data is largest and most dis-functional market Brad has seen. There is a lot of change and small companies can move fast, but big companies have more trust & money (both important)
The most obvious moat is data; there is a lot of fear about these models from the big companies. Where is my data going?
Finished with 10 questions - some personal questions that will give you some background and Brad and his motivations
Highlights (52-minute run time):
Minute 03:30 – interview starts; NOMAD background
Minute 06:30 – what is now possible has grown in the last 6 months
Minute 07:00 – what is the problem that NOMAD is solving?
Minute 09:45 – how to describe the data in business language?
Minute 12:30 – next phase is not personal data but “everything data”
Minute 15:00 – how will this access to data change co’s, both large & small?
Minute 18:30 – screen share NOMAD (not ideal for Spotify listeners)
Minute 25:00 – who are the early adopters of the NOMAD platform?
Minute 30:30 – 10 questions for Brad
Minute 44:00 – what do humans need to be thinking about re: the future of AI
Minute 48:00 – LinkedIn as a resource for learning
BONUS: Building The World’s Best Data Drilling Operation with Brian O’Keefe
Source: BattleFin & Andeco published their annual State of the Market Pricing Report. January 2024.
Connect with Jordan Schub at BattleFin to learn more (jordan@battlefin.com)
75% renewal rate (is that good?)
This is higher median than I would have expected.
We get asked about this A LOT (call me … we can help!):
Research Ready
Theme that emerged in this week’s email is … Data is tough to “get right” but pays off when you do.
One of the features of big data that make it tough is simply understanding what you’ve got (AKA meta data). Data engineering takes a majority of the time and resources available. How is the data being delivered?, what quality checks are in place?, is anything missing?, is the vendor meeting the SLA requirements? … the list goes on.
Babel Street | Vertical Knowledge is now offering a growing list of Research Ready “refined products”. We do the heavy lifting for you. We clean, normalize, & organize the data so you can focus on the fun … analysis, asking good questions, building conviction in your investment case.
Available today (more to come!):
Real Estate
Self-Storage
Retail
Footwear
Handbags
Flights
Locational Whitespace (compare locations of competing institutions overlayed with granular demographic info)
This list is growing quickly. Contact me to learn more.
Handbags (8 distinct brands)
Sneakers (9 brands across 8 distinct retailers)
Locational Whitespace (sample CVS, Walgreens, RiteAid)