Alternative Data Weekly #127
March 31, 2023
Thanks for being here!
Announcement(s):
Our transaction data is now available at more granular “row level”. 4+ years of history. Daily data.
90 West re-launched Cross Country Insights this week.
If you care about RBLX (the stock), you should be checking out our Gift Card Data. We have found the elusive Product-Market FIT.
Contact me to learn more.
Theme that emerged in this week’s email is … AI hyper-attention is reaching crypto-bubble levels…is it justified?
Sidenote: OMG there was A LOT written about AI this week.
QUOTES
“Start by [AI] making recommendations that are reviewed by humans. If those are correct and have the desired impact, eventually we will build trust and reduce the required level of supervision. Ultimately, we will reach a point where the AI has been right so many times, that we can allow it the autonomy to automate optimizations with minimal supervision. The stages of maturity can broadly be described as: observing, reporting, recommending, optimizing and predicting. The last three are where augmentation is applied,”
Adam Ronthal, VP Gartner ITL Data & Analytics Group (quote cited from this article)
News Articles
Podcasts
Cool Charts
Final Thoughts (Less Impressed, More Involved)
#1 – VentureBeat published How AI can ease those data management woes. March 2023.
My Take: This is real. I’ve been using ChatGPT almost every day for the past 4-6 weeks to help improve code. Functionally, this allows me to spend more time thinking about the questions I ask the data rather than managing the data itself. This is a much higher impact use of my time. There is real-world value-add to be had from AI as it continues to improve. Frameworks such as those presented in this article are helpful to get started. … start with observing, move to reporting, recommending, optimizing, and eventually predicting.
#2 – Alex Izydorczyk published Dumb Questions about Artificial Intelligence. March 2023.
My Take: AI relies on data. Data owners and those that have data organized & ready to be used will benefit. There are a ton of questions that remain to be answered, but we are on the front end of this wave. Data owners are well-positioned.
#3 – Jason English, Principal Analyst at Intellyx, published DataFinOps: More on the Menu Than Data Cost Governance. February 2023.
My Take: FinOps + DataOps = DataFin Ops(?). It is tough to get a definitive ROI for those firms looking to understand the data monetization opportunity. Often there is quite a bit of investment just to get your arms around what you’ve got, much less understand the market value of your data. This investment is well worth it, even if just to make better use of your own internal data.
BONUS: Per Nymand-Andersen, Emeritus Adviser, European Central Bank, hosted a training session titled Big Data and Data Science: New Opportunities in Reporting, Forecasting and Policymaking. March 13-16, 2023. Introduction letter here. If anyone reading this note attended the session, I’d be interested in learning more about the program. Thanks!
BONUS 2: Intel & Aible published Case Studies from the "Impact from AI in 30 Days" Program. March 2023.
BONUS 3: From Bill Gates: The Age of AI has begun.
BONUS 4: Check out this data storytelling survey from Abe Gong.
#1 – John Kutay of Striim published this interview: Hot Topics in Data with Ethan Aaron from Portable.io. March 2023.
My Take: Good overview of the data space and current trends. Of most interest to me was Ethan Arron’s four (4) ways to create value from data: 1- analytics, 2- operations (streamline some manual process), 3- build products people pay you money for, and 4- risk mitigation. Good quote attributed to Juan Sequeda of Data.world … this is a “show me the money year” for data.
Highlights (34-minute run time):
Minute 02:20 – interview starts, overview of hot topics
Minute 02:45 – first, macro & how that ties back to data landscape (job market outlook)
Minute 06:00 – as a data practitioner, how do you differentiate yourself?
Minute 10:30 – data contracts, producers, or consumers on the hook?
Minute 17:00 – will data companies consolidate?
Minute 26:00 – predictions for 2023 (more conflict amongst the big players?)
#2 – Alex the Analyst published ChatGPT for Data Analysts | Best Use Cases + Analyzing a Dataset. February 2023.
My Take: I use ChatGPT a lot for explaining and (importantly) optimizing the SQL code I use. This allows me to focus on asking better questions of the data rather than getting the code right.
Highlights (31-minute run time):
Minute 01:30 – feeding ChatGPT a prompt (can explain code really well)
Minute 05:30 – sample of SQL code request
Minute 08:15 – importance of commenting code
Minute 09:30 – creation of data dictionary
Minute 11:15 – optimizing code using ChatGPT
Minute 14:00 – Analyzing datasets (several examples)
Source: Much better version Auren Hoffman’s Data Business matrix that I posted last week:
Source: Less Impressed, More Involved
I came across this saying in the book Greenlights by Matthew McConaughey (I really enjoyed this one BTW).
Spend less time admiring from afar. Spend less time in awe. Spend less time being amazed at another accomplishment.
Get involved.
Even when working with people like Martin Scorsese, McConaughey would say there is no magic. You have to do the work.
Want to be a writer. Write.
Want to be a coach. Coach.
Want to be a stock trader. Trade.
You have the greenlight.
If you not a starter and you think you should be, give 'em no choice in the decision. Play so well it's undeniable.
BONUS:
h/t Benjamin Rogojan & Scott Adams (of course):
