Learning – Eric Frayer.com

July 31, 2023

GPT-4 and Code Interpreter are hotter than Barbie!

Happy Summer! I’m looking forward to seeing Oppenheimer and Barbie on vacation next week. Both are summer blockbusters which are hot, hot, hot! Explosive and blowing up everywhere. So… What could be bigger and a “real-life actual” game changer?
Generative Pre-trained Transformer (GPT-4) and Large Language Models (LLM’s).

It’s hard to describe how jaw-dropping Open AI GPT-4 Plus is and for only $20 per month how it can change your life. The ability to load a dataset, run analysis, plot the results, and have the python code available with narrative describing the rationale behind advances statistics is unbelievable. It’s clean, fast, and overall, technically accurate. Note: I’ve executed the python code generated by GPT-4 in my own Jupiter notebook and Visual Studio Code to check the results.

I’ll post additional thoughts on my node.js Azure sandbox but don’t wait for me – go get a subscription and try it out for yourself!

April 20, 2023

Data Warehouse, Data Lakehouse and Data Mesh

Last year, I read a very interesting blog post by Darwin Schweitzer a Microsoft technologist who discusses how to consider emerging technologies in the context of building sustainable enterprises. The blog posts relates the learning patterns organization adopt to newer data technologies replacing existing capability. The approach covers the strategic, organizational, architectural and technological challenges and changes with scaling enterprise analytics.

Three Horizon Model/Framework – strategic
Data Mesh Sociotechnical Paradigm – organizational
Data Lakehouse Architecture – architectural
Azure Cloud Scale Analytics Platform – technological

https://geoparquet.org/ is worth checking out!

Recently, I watched a webinar hosted by TDWI, Databricks and Carto. The topic was Unlocking the Power of Spatial Analysis and Data Lakehouses. A copy of the webinar and the slide deck shared is available here. What I liked about the session was the use of Databricks and a Data Lake to provide Spatial Data. There was also a brief discussion on the role of the Open Geospatial Consortium. This group is working on the specifications for creating a geoparquet file. For anyone with an interest in GIS, Mapping, Data and Analytics this is worth checking out!

https://github.com/opengeospatial/geoparquet

January 18, 2023

ESRI Tapestry Segmentation

For the last 20 years, ESRI has been capturing geographic and demographic data. In the 90’s Acxiom (and others) came up with Lifestyle Segmentation. ESRI started in 1969 and today maps “everything” down to the household level.

I’m surprised by the accuracy of Tapestry Segmentation. The top three segments in my zip code are: “Top Tier”, “Comfortable Empty Nesters” and “In Style”. Pretty accurate – with one data point. I’m an Empty Nester who would like to be “In Style” or “Top Tier” but feel very lucky and fortunate to be “comfortable”.

Here is a link to a PDF with more on Tapestry Segmentation and my personal segment.
Just in case you we’re interested here are the details on “Top Tier” and ‘In Style“.

January 31, 2022January 31, 2022

Modern Analytics Architecture

Microsoft provides valuable documentation on how it sees the Modern Analytics Architecture evolving. More information can be found at the link below:
Modern analytics architecture with Azure Databricks – Azure Solution Ideas | Microsoft Docs

April 16, 2020

Nathan Yau’s Reading List

I follow and really like Nathan Yau. His site FlowingData.com is a great resource for Data Visualization inspiration. Below is his reading list for during the crisis:

Making Charts

Books specifically about making and using charts…

Info We Trust by RJ Andrews — Unique because Andrews hand-drew all of the examples himself.
Data Visualisation by Andy Kirk — It’s next up with the Datavis Book Club.
Designer’s Guide to Creating Charts and Diagrams by Nigel Holmes — I bought a used copy a while back for a couple of dollars. I’ve always admired Holmes’ style.
Wordless Diagrams by Nigel Holmes — Got this one too, pretty much for the price of shipping.
Elevate the Debate edited by Jonathan A. Schwabish — A practical guide aimed at communicating technical research to a wider audience.

Statistics

Making sense of numbers…

Factfulness by Hans Rosling — I’ve heard many good things. Probably first up in my queue.
Exploratory Data Analysis by John Tukey — It’s an outdated textbook but it’s historically rich. I’ve never read it cover-to-cover.
How Charts Lie by Alberto Cairo — So important these days.
Understanding data and statistics in the medical literature by Jeffrey Leek, Lucy D’Agostino McGowan, and Elizabeth Matsui

Development

Some code…

R Packages by Hadley Wickham — I know the basics, but I should know more.
The Book of R by Tilman M. Davies — A big, fat reference.
Some visualization with Python book. I’ve seen some books, but is there a well-regarded reference?

Design

Outside visualization, but applicable…

The Shape of Design by Frank Chimero — Got this years and years ago. I will assume it has aged like a fine wine.
The Design of Everyday Things by Don Norman — Charts are everyday things.
Emotional Design: Why We Love (or Hate) Everyday Things by Don Norman
Understanding Comics by Sott McCloud — Telling stories visually. Sounds familiar.

Inspiration

To think about various visual forms…

History of Information Graphics by Sandra Rendgen and Julius Wiedemann — This is a giant book with giant pictures.
All Over the Map by Betsy Mason and Greg Miller — The stories behind the visuals always make the picture more interesting.
How To: Absurd Scientific Advice for Common Real-World Problems by Randall Munroe — I admire Munroe’s ability to explain things with stick figures and clear diagrams.
Math With Bad Drawings by Ben Orlin — Again, interested in the process more than I am in the material.