Thanks for being here!
Theme that emerged in this week’s email is … data quality is a big deal.
QUOTES
“The more appropriate insight use cases addressable by the data vendor, the more valuable the data becomes.” - Jason DeRise
“Collaboration becomes harder as no one is familiar with the entire code base. Time spent in meetings goes up relative to time spent getting things done.” - Mikkel Dengsøe & Louise de Leyritz
News Articles
Podcasts
Cool Charts
Final Thoughts (Gen Z Kids)
#1 – Jason DeRise published in his The Data Score newsletter 8 point approach to evaluating data partners. May 2023.
My Take: There is a ton of friction in the process and Jason does an excellent job of describing the keys steps. From the data vendor perspective, the cleaner & easier you can make this process, the better. Clearly describe the value your data adds. Make it easy. And of course, Jason highlights the importance of data quality. You know your data better than anyone. Be transparent about strength & weaknesses from the beginning.
#2 – Ashu Dhall published Why Do Chief Data Officers Deserve a Seat at the C-suite Table?. May 2023.
My Take: Are CDO’s defensive-minded or offensive-minded? Ashu argues good CDO’s balance the two mindsets. You are likely to get more C-level respect if you are driving revenue & innovation for your business.
#3 – Mikkel Dengsøe & Louise de Leyritz published in Synq’s blog The struggles scaling data teams face. May 2023.
My Take: Good article covering the challenges data teams face with scale around onboarding, development, monitoring, and self-serve. In particular, I like the idea of simplifying (clean up what is not needed) & being relentless focus on building trust.
BONUS: IMF Climate Capacity Development (CD) Partnership Forum—First Meeting. May 2023. “…we are working on making quality climate data available through the IMF’s Data Standards Initiative and the G20’s Data Gaps Initiative—because good data is essential for good decisions.”
BONUS 2: Monte Carlo’s Barr Moses & Shane Murray published Zero-ETL, ChatGPT, And The Future of Data Engineering. May 2023. “The endless reimagination of the data lifecycle”
What else I am reading:
Byrne Hobart published Three Models for Data Companies. Paywall. May 2023.
Bloomberg News AI presents nearly level playing field for startups and big tech. March 2023.
Semianalysis’ Google "We Have No Moat, And Neither Does OpenAI". May 2023.
Hex’s blog published Don’t Tell Your Data Team’s ROI Story. August 2020.
Benn Stancil’s BI by another name. May 2023.
#1 – Rebellion Research interviews Peng Cheng, Head Of Big Data & Ai Strategy JPMorgan. April 2023.
My Take: Good, short interview. I remain interested in learning about “real world” use cases for the buzzwords like ML, AI, etc.
Highlights (6-minute run time):
Minute 01:00 – interview starts.
Minute 03:00 – how is Peng using machine learning today at JPM
Minute 04:30 – Peng shares examples (“optimizer at the end of the day”)
#2 – Auren Hoffman’s World of DAAS podcast interviews Will Manidis is the CEO and founder of ScienceIO. May 2023.
My Take: Very dense interview. Not one to listen to at 2x speed. Lots of great quotes. I agree that the “mean industry” has not seen (much) technological progress. I think there is a generational element where younger generation that have grown up with “technology tools” will bring this comfort with them to industries that are not yet using technology to their greatest advantage.
I am interested in this as Will’s company ScienceIO is working to make better solutions for healthcare data. I am currently working with a healthcare dataset and am dealing firsthand with those challenges.
“Going from unstructured natural language to structured information that is readily computable is a generational platform shift.” - Will Manidis
Highlights (36-minute run time):
01:00 – intro and the interview kicks-off
02:50 - unstructured enterprise data ready for computation workflows.
04:00 – “messy middle of tasks that are a thorn in your side have resisted innovation”
07:00 – solving problems at the government level
08:30 – optimists vs pessimists (is there a shortage of optimists?)
10:00 – what do people not appreciate about building these LLM systems?
11:00 – “chat is a bad way to interface with most problems”
13:45 – how important is it underlying data is “true” (again …this data quality theme)
16:30 – knowledge workers will have radically better tools in the future
17:45 – “You will become co-pilots to computational systems”
18:30 – innovations that are coming in healthcare (gatekeepers, inefficiencies, etc)
21:30 – discussion of privacy, HIPPA (too hard to move data out…work with data where it lives)
23:00 – discussion of poor outcomes: “…damage done to middle of country … fix the spiritual rot before we can fix anything else”
26:00 – relatively easy way to see big change … just bring technology to provider workflows
26:30 – should more people broaden research? People should pick up more hobbies; the upper-middle-class kid is super-tracked; Universities doing a good job destroying themselves …
28:45 – what is the cause of the “curse of preference falsification”; “We place a high value on being nice to each other at the fault of getting things done.”
30:30 – do demons exist? “Functional benefit of religion is it limits the amount of questions you have to ask”
33:00 – David Foster Wallace: “There are no atheists” … tribal vs religious
From
Source: Crux published The External Data Maturity Model. May 2023.
The external data maturity model is designed as a tool to assess where an organization falls on the curve and provides a roadmap to help companies plan for their future state.
Source: Do the Kids Think They’re Alright?
“These Kid’s Today!” (insert eye roll) - quote heard from every previous generation
As the parent of Gen Z kids … I am curious how this group is developing. They are growing up very differently than any previous generation, mostly due to the phone & constant connectivity. This article did a good job addressing some of the challenges & opportunities, from the perspective of the younger people themselves.
Every generation has has their headwinds. This group will be studied & judged more closely than any previous generation. We simply have more data.
My general sense is those kids that use the tools (socials, AI, tech in general) for good will thrive. Those that let the tools (socials, AI, tech in general) use them, will struggle.