Preamble
One day I decided to ride my bicycle 100 miles on 1 gallon of water. I did it, all the while remembering my high school chemistry teacher that always complained about the fuel inefficiency of cars.
Back in the late 1970’s, he was saying that our cars should be getting 50 to 70 miles per gallon of gas. So on that particular day of spinning out 100 miles on 1 gallon of water, with only perspiration and carbon dioxide as byproducts, I designed a tee-shirt. It simply said on the front side: “100 miles!” On the back side it said: “per gallon of water”. There was a bicycle picture below that. One day I need to make that tee-shirt!
Introduction
Looking backwards in time, I can see very clearly how I have migrated into my current career. For you to understand this too, you should read my previous Tableau short story before reading this one. They are intimately tied together and explain why I am doing what I am now doing in my professional career.
Background
My big data vehicle dream started on a day in late February 1996. I was getting set to move to Vicksburg, MS, to work the summer at the Waterways Experiment Station (WES) as a consultant. Before moving, I bought a 1996 Black on Black, 5-speed Nissan Maxima that provided the experimental unit to fulfil my big data dream.
For over 8 years, I recorded every drop of gas bought for the car, every mile driven. That took a lot of perseverance to do. If you want to understand why I did it, I encourage you to read the articles I wrote about the experiment and the results. To fully appreciate my story, reading these is important.
What Does This Have to Do With My Current Career?
It is obvious from the 1985 and this story from 1996, that I have been a fanatic about vehicle performance for over 30 years. In fact, the very first computer program I ever wrote on an IBM PC in 1979, had to do with calculating performance metrics of me riding my 10-speed bike. Now with that thrown into the mix, I’ve got nearly 40 years of documented experience pointing me in a particular direction. That direction is now what I do in my professional career.
Over three years ago, General Motors found me, picked me up, and slammed me out of my comfort zone. The ride I have been taken has fulfilled my dreams. I guess you can say I have landed exactly where I wanted to go. I work for a great company, doing very interesting work, with each working day passing in minutes.
I blast through vehicle performance data that is flying at me with increasing speed. Ten million, then eleven million vehicle trips per day are there for me to analyze. Hundreds of thousands of new cars being thrown into the mix every month. Billions of miles being driven in dozens of GM models by millions of drivers every year. It’s all in my field of view. Thanks to the combined usage Alteryx and Tableau, I can easily handle it and derive huge insights at multiple scales and from many different perspectives.
This experience is insatiable. It’s like finding the girl of your dreams (I did that too!), and then getting to live your life with her. It’s another sort of marriage for me, one that I have been thinking about and practising for all of my life.
When GM first contacted me about a potential job, when I heard that streaming vehicle data was one of the projects I might work on, I asked where to sign up. Now I’m hooked, engaged, and look forward to each day with the eagerness of a kid in a candy store. There are so many interesting findings to be uncovered, that I know the job will continue to entice me for years to come.
If you are a reader of the blog and take the time to read my more technical articles, you will see bits and pieces of my methodological discoveries hidden in techniques I publish. As usual, I cannot discuss specific results, but I can surely talk about how my dreams have come true thanks to General Motors.
Thanks for reading short story #3.
