The Grapes of Data
A Tale of Two Trade Crafts
In discussing data, I have used a wine analogy or two. This article will go much farther. It is an analogy in five parts. It is one that starts by getting a little dirty but quickly develops into something exquisite and refined.
Dirty Data Or Is It Terroir?
We have all heard the woes of dirty data. All data is dirty. Duplicates and nulls, test records and noise — data can be a mess.
But as an analyst, I prefer my data to have its terroir intact. Yes, I have a snobbish view of all that dirt. It tells me much about the nature, context, and landscape where my data was created. While I might chose to remove that dirt in the refinement process, I want to make that decision. I don’t want my data purged or filtered unless it is by my own hand. I really don’t want dummy values added that will ruin everything. It is a point of view that vintners and I share.
Cultivation Requires Structure
Spend some time in a vineyard and you quickly realize that little in the cultivation process is left to chance or nature. Vines are pruned, structured, and supported during the cultivation process. Grapes need this to produce the best wines and your data needs this to produce the best insights. There are plenty of parallels here. Time, patience, and centuries of experimentation have brought us the trade craft we have today.
Distillation — A Beautiful Science
We don’t often consider the vast amount of chemistry and science involved in distilling alcohol. We more often think of it as experimentation and taste testing.
Interestingly, both concepts figure into data and analytics as well. Though analytics is more readily associated with mathematics and equations, quite a bit of it remains head to head testing and basic comparisons. In the end, rules regulate the conversion of sugar into alcohol and data into insights.
Complexity Is Best Appreciate By A Refine Palette
Wine celebrates complexity a little better than analytics. Complex analytics are much harder to appreciate. But then only a refined palette truly experiences the full complexity of a great wine. For everyone else, we just know it is good.
Artificial Intelligence and Data Science are the new buzz in analytics. But most people really don’t understand the complexity, nuance, or quality of these highly refined analytic techniques. They just like the look and taste of the final product.
If Only The Data Warehouse Was As Much Fun As The Wine Cellar
With experience, time, and maturation — complexity becomes more subtle, more refined, more elegant. It is like the synthesis process in analytics. If distilling wine is the breakdown of sugar into alcohol, maturation is the creation of something special. In the wine process, new compounds are created. The chemistry changes, oxidizes, and crystallizes. The framework and time applied by the vintner has created something special. Data is no different.
This analogy could continue on. From specialized storage and transport to wine pairings and other preparations — there are plenty of other creative parallels. But the story that we set out to tell has developed — a tale of two similar trade crafts.
Recognize the value of data’s terroir. It gives it a unique signature and that can have value. Take pride in the cultivation process — the need for structure, prioritization, and support. Distill your data into information and insight. It will require trial and error — but is always based in science. Learn to appreciate the complexity but spend the time to mature and synthesize those insights. The final product will be delicious and intoxicating — I am talking about the wine, but the insights you create will be pretty awesome too!
Thanks for reading!
