Zen and the Art of Data Analysis

Posted by HR Analytics on Friday, October 4, 2013 Under: Data

Data analysis, just like motorcycle maintenance, when performed properly can provide satisfying and gratifying results.  For many analysts, the journey through the analyses is just as satisfying as uncovering and finalizing the results.  There’s something about the data analysis steps that keeps analysts plowing through, discovering and uncovering revelations from the data.  

“Zen and the Art of Motorcycle Maintenance: An Inquiry Into Values,” written by Robert M. Pirzig is a very profound philosophical timeless classic that has so many applications in many of the journeys we take in life.  Believe it or not, data analysis is one of those journeys that can use the wisdom found in this book.  Although this book is about a motorcycle trip that really is about a journey through the thousands of years of great ideas and philosophy, through the complexities of the world around us, and through human life, in more ways than one, the analogies, symbolisms, perspectives, and philosophies are very applicable to the “art” of data analysis.  

So here below is a compilation of some of my favorite quotes from the book that often resonates with me when I do data analysis.   

“Is it hard?'

Not if you have the right attitudes. It’s having the right attitudes that’s hard.”

Imagine all those rows and columns of noise.  Data analysis can be overwhelming, intimidating, and boring but analysts need to have that attitude to drive them to dig in and look for meaning in what the data is saying.

“You look at where you're going and where you are and it never makes much sense, but then you look back at where you've been and a pattern seems to emerge. And if you project forward from that pattern, then sometimes you can come up with something.”

Trends analysis

“For every fact there is an infinity of hypotheses. ”

The sex ratio for the entire world is 101 males:100 females.  Imagine all the possible hypotheses around that.

“The truth knocks on your door and you say, "Go away, I'm looking for the truth," and so it goes away.”

Predetermined queries?  Got some presumptions before diving into the data? Don’t get too hung up on those presumptions and miss out on what other results might come up.

"Sometimes it's a little better to travel than to arrive”

Data analysis can sometimes be a never-ending task. You may find answers to the question you originally set out to answer but new questions may pop up.  There’s always something else that will emerge and such quest can often be exciting.

“Who really can face the future? All you can do is project from the past, even when the past shows that such projections are often wrong.”

Despite standard error and confidence interval calculations, projections are just that and are still subject to being all wrong.  

“We take a handful of sand from the endless landscape of awareness around us and call that handful of sand the world.”

Does a summary of findings really do justice to an entire dataset?  Sometimes these results are just the tip of the iceberg.

“When analytic thought, the knife, is applied to experience, something is always killed in the process.”

Any person is not just a statistic.  

“The real purpose of the scientific method is to make sure nature hasn’t misled you into thinking you know something you actually don’t know.”

Scientific method is definitely a useful approach in virtually everything we do.

“Other people can talk about how to expand the destiny of mankind. I just want to talk about how to fix a motorcycle.”

In this complex system we are all in, we often think we can solve big picture problems and come up with a model that captures it all, from the top down.

“Although motorcycle riding is romantic, motorcycle maintenance is purely classic.”

Producing and delivering the findings and the results of a data analysis can be quite satisfying but there’s also something quite enjoyable in the process of data transformation, manipulation, merging, correlating, and connecting the data.  

In : Data 

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