Using Alteryx To Understand Climate Change
This is my second appearance on the Alteryx podcast. In this episode, I talk about my decade of work on climate change. It isn’t very technical, but I hope people appreciate the insights.
The Timing of Global Warming Development
This article investigates the sensitivity of my global warming simulator to the length of the simulations. I wanted to understand if 10, 20 , 30 or more years of data would be required before stable temperature predictions would be achieved.
Article 400 – Decoding The Global Warming Book
This article summarizes eight years of global warming research. It also happens to be my 400th article. There is a lot of information packed into the links.
Global Warming Insights In Small Pieces (Part 3)
This is part 3 of a story that documents a recent trip to California.
Truthful Global Warming Insights
Eight years of data-driven global warming research is wrapped up in this article. You can unpack a half-a-billion data points in this article to explore the ideas for yourself. You can download Tableau dashboards that will teach you a thing or two about linear modeling. Most of all, you will gain a better understanding of what is going on across our beautiful planet if you take the time to study this work.
Global Warming Insights In Small Pieces (Part 2)
We were already down two strikes by the end of day 1. Mother nature was throwing curveballs at us that we could not have hit. Who would have thought that a National Park could be on fire on the day that you traveled thousands of miles to see it?
Global Warming Insights In Small Pieces (Part 1)
This is going to be a multi-part story about my global warming research and how my insights can be interpreted and understood. I think this series will be a good one.
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The Alteryx Advantages
I’ve been using and testing Alteryx for eight years. I’ve made tens of thousands of Alteryx runs. I’ve experienced thousands of hours of compute time. What have I learned? You will need to read the article to find out.
A Useful DMA Shapefile For #Tableau and #Alteryx
In this article, the technique of polygon generalization is used to reduce the complexity of DMA boundaries. This boundary change makes preparing and displaying DMA-based data much faster in Tableau.
Results of Big Data Experimentation With #Alteryx and #Tableau (Part 1)
This article discusses testing of the new Alteryx AMP engine. The Alteryx Multi-threaded Processing (AMP) engine has shown excellent computational speed improvements during the past few months of testing.
How To Rapidly Retrieve Data From Large Data Sets Using @Alteryx
Alteryx has a secret weapon when working with large data sets. This weapon is called Calgary files. In this article, I show an example of using Calgary files.
I Wonder What is Causing This Weird USA April Warming and Cooling Pattern
Today is Earth day which reminded me that I wanted to talk about a peculiar temperature change pattern I’ve detected. I don’t have the answer of why it has occurred over a four-day window in April. This pattern is revealing itself over 60 years through millions of temperature readings. Be sure to get to the end of the file to see the baby birdies!
How Colton’s Accomplishments Became One of My Proud Moments in 2019
This story spans more than two decades. I have watched our beautiful baby boy grow up to be a fine young man. It is now time for Colton to find his place in the working world. It is my hope that he is able to find a job that will allow him to use his education and creativity to do great things for the company that hires him.
How Alteryx Took Me to the Edge of Comprehension and Sanity But Tableau Saved Me
Learning to solve complex problems takes time, practice and patience. It also requires great software like Alteryx and Tableau. For the past two months, I’ve taken a deep dive into a naturally complex system. I feel like a deep diver that needs to come up for a breath of fresh air.
Why @Alteryx and @Tableau Are Sticky Products
It has taken me a while to understand something important about Alteryx and Tableau. Each of these products are very sticky. By sticky, I mean that I have become dependent upon them to do a lot of different jobs. They both are great products for different reasons, but the combination of them is hard to beat when working with data.