Why a blog?

Frequent advice I read on tech-X is that blogging and writing down your thoughts is a great way not only to build an audience, but to find potential new job opportunities and also sharpen your own skills; forcing you to think through how you would communicate a technique or idea simply allows you to understand a concept better.

No one really seems to argue with this when it's brought up. It just feels to difficult to actually start.

I've never been excited to sit down and write, and I'm hoping that this helps to change that a bit. I love to teach, and this can act as an extension of that in a life that I don't get a lot of opportunity to do much teaching.

But first, an intro...

My name is Patrick Hennessey, and I love to build. Building started with Lego kits connected to VCR motors harvested from discarded electronics found at the curb in elementary school. When I was in middle school, I became more interested in bigger structures, with a tree fort taking shape in our back yard. This quickly escalated to a larger multi-tree structure when my dad go involved, and then became too difficult to actually complete. And so we became proud users a platform two stories in the air rather than a true tree house.

Once in high school, I learned that turning wrenches on cars was where I was most interested. A group of friends introduced me to the Honda/Acura tuning scene, and I saw junkyard cars turn in racing machines. This was probably the first time I realized that you with enough no-how, you could take something cheap and have an absolute blast with it.

While I studied Behavioral Neuroendocrinology in graduate school, I found so much joy in building the machines we would use to study animals in the pursuit of knowledge. Again, it demonstrated to power you could wield being a creator, a builder, and manufacturer of tools. It could set you apart from your peers that were forced to rely on preconfigured or off the shelf products.

When I had an opportunity to take some time off and do some directional drilling during the North Dakota oil boom, I decided to take it. And low-and-behold, it was assembling hardware and configuring measurement-while-drilling (MWD) tools that kept me so interested in that!

Whatever I end up doing, I always find my joy in doing it when I'm building.

Finding Tech

My career has been a data-centric one. I spent the first half of my career working for various consulting companies around the Denver area delivering enterprise data engineering and analytics solutions. I found a lot of success doing this, and built a reputation for fitting square pegs into round holes, and doing so very quickly. In hindsight, I wish I had spent the earlier part of my career working with web development or backend software engineering to give me an opportunity for machine learning jobs as they started to come out 10 years ago, but I focused on what I had already found a natural fit for. Without an academic background in CS, it was harder to wiggle your way into one of those other careers at the time, and what I was doing worked

So what? Why is this relevant?

This is a good question, and one that sometimes I ask myself immediately after launching into my background. The best I can come up with is that over the course of my youth and adult life, I built a lot of stuff. I think a solid 80% of it was useful the moment it was finished/delivered/implemented, and more than 50% was still in use after 2 years.

This may seem like low numbers, but anyone delivering data technology to customers should be impressed with this. Much of 20% of projects that ended up not being useful took too long, or I had my blinders up to what really should have been delivered in the moment. Often times those two things are actually innately intertwined. Some of it is because of constant executive turnover turning this last boom in the start up space.

And of all these projects, the ones that I see working the best, for the longest periods of time, with the least amount of constant maintenance are those that have been designed with data in mind. I worked for two startups with billion-dollar valuations leading their analytics journey, and I came to find this lesson out the hard way. When data is just something that happens after someone uses your application, your analytics will smell like what happens after we eat food - and there isn't much your data team can do about that.

So I'll be writing about a data-forward way of delivering tools and applications, and discuss tech I think is important along the way. I hope you'll stick around and read once in a while.

Patrick