Educate the cabbage and train the almond

Training is everything. The peach was once a bitter almond; cauliflower is nothing but cabbage with a college education.-- Mark Twain

I recently returned to a vegetarian lifestyle. The request came from my biologic clock. I am one of those annoying morning people. I like to hit the pavement or the pool to help clear my mind and set up the day.

Although I have a  pretty deep well of energy--my workouts were sort of "meh". The morning run became more about exercising my hound, trainer rides on the bike were to appease my guilt over watching too much Bravo TV--"hey I am riding 40 miles, don't judge", and the swims were often to calm a busy mind. In other words, the goals were ill-defined and mushy, figuratively and literally.

Thankfully I developed a podcast habit to accompany me on the long runs. I may be out of the office but on a cellular level, I am thinking, designing, and creating new possibilities. Rich Roll had been one of the podcasts I thought didn't match my prior meat-eating on again, off again triathlete lifestyle. But I was wrong.

He said something a few episodes ago that really resonated and even tugged at my professional life.

You need to train, to train.

I imagine it will mean something different to everyone but as a former age group triathlete, runner, and cyclist I had been mourning the strength and speed I once had. I told my coach to never assign workouts with swim fins. He asked me why. I said, "because they told me I was fast" and "they lied".

​I didn't want a crutch I wanted to return to basics. I needed to rebuild my foundation. I am only in week 3 of lifting the weights again and returning to a structured work out regimen. I don't let deadlines or busy data projects, speaking engagements, or anything interfere.

Keeping with the theme of evolving into a cauliflower--I also decided to refresh and expand my computational skills. When I was studying statistics we didn't have fancy calculators or computers at the ready. We did most of the calculations by hand or on simulators. Many colleagues at statistics conferences share similar stories. Especially with real world data and advanced modeling new to all of us. These weren't on the horizon when many of us were in our post-graduate studies.

Databases are everywhere and there is a keen interest in linking disparate data sources. Luckily I am a busy datapreneur but what if there are efficiencies out there to improve scalability?

I hope you are also continuing to step outside the comfort zone.

​The view is better out here on the periphery! Leave the middle for average and ordinary...