Brent LaRowe

Good decisions start with good data. Whether you're running a multi-million-dollar organization or just trying to optimize your home’s energy use, the same principles apply: you need accurate, clean, and well-governed data to make meaningful choices.

So in the past, I crunched the numbers to determine how much heat my home actually needed, even on the coldest days of the year. That was step one. Step two? Figuring out whether switching to a heat pump made financial sense.

Sometimes, an update breaks something, and no amount of troubleshooting seems to fix it. That’s what happened to me after a recent Docker update and a Nextcloud AIO Mastercontainer update. Suddenly, my externally mounted drive setup for Nextcloud’s data path stopped working. I tried to troubleshoot the issue, but after running in circles, I decided to take a different approach—ditch AIO and rebuild my Nextcloud deployment using docker compose.

I love digging into data, and while I am a certified data analyst, my day job is more in the data structure and usefulness. I’m just someone who appreciates the power of numbers and the insights they can reveal. I also rely heavily on other smart people who share their data science knowledge online, which means there’s always a chance I’m misunderstanding, misapplying, or just missing a better way to do things. But, in the spirit of transparency, here’s how I analyzed my home’s furnace runtime using R.

HVAC professionals know their stuff. They have specialized tools, years of experience, and deep knowledge of heating and cooling systems. When you hire one, they’re going to get the job done. But what exactly are they experts in?

Good data analysis starts with good data collection. I needed reliable, consistent data on my furnace’s actual performance. I assumed this would be simple. It was not.

When I set out to determine whether my 145-year-old home was a good candidate for electrification, I knew I needed to go beyond assumptions. So, like any good data nerd, I fired up R Studio and got to work. What I found challenged a lot of conventional wisdom and gave me a much clearer picture of what my house actually needed to stay warm in the winter.

I’ve spent nearly two decades wrangling data -- cleaning it up, organizing it, and making sure the right people could actually use it. Back when I worked at the UChicago, my job as was to ensure that information flowed smoothly, was reliable, and didn’t get lost in bureaucratic chaos. That experience drilled into me one simple truth: data isn’t useful unless you actually know what to do with it.

I grew up in a snowbelt of Northern Michigan in the 1990s. It had this strange dichotomy of identity -- both rustic and refined, somehow. Traverse City is a very popular tourist destination, and as such, had a number of things that are close to urban-istic; and on the same token, I lived and worked in environments that demanded care and understanding to prevent a car from becoming inoperable several miles away from anyone that can help. But that "rustic" aspect taught a person that they should have various resources on hand, just in case, and that easily translated into making choices about everything from clothing to vehicles to home improvements based on the "just in case" situation. It was better to have waterproof boots as your main footwear just in case the weather turned terrible and the parking lot was full of slushy snow. It was better to drive a vehicle with good clearance and four-wheel drive just in case a blizzard hit and you suddenly had to drive through feet of snow on your way home.

Take a minute to consider your sandwich. The bread, the meat, the cheese. Perhaps some lettuce and tomato. The proper sandwich is also adorned with pickles, mayonnaise, and mustard; perhaps you have an improper sandwich. Think about it like Carl Sagan thinks about pies. Look at each piece of your sandwich and see its path backwards in time. Go further and further back, and you eventually get to the spot where every part needed some sunlight in order to use water, carbon dioxide, nitrogen, and minerals to make itself. Even the ham or pastrami needed a plant along the way.