Wine May Be Romantic But Data is Sexy: A Guidebook to the Future
What’s the sexiest job of the 21st century?
If you believe the now-iconic Harvard Business Review article from 2012, the answer is data science.
Data science as sexy? The dating profiles for data scientists never looked the same again.
At least not according to Jennifer Priestley and Robert McGrath, the wise and wry co-authors of the new book Closing the Analytics Talent Gap: An Executive’s Guide to Working with Universities. They say that the article naming data science is regularly cited as kickstarting the national conversation about data science. (And a whole lot of updates to dating profiles.)
That’s the one that, a few years later, Enolytics stepped into. As I wrote in this week’s book review of Closing the Analytics Talent Gap, we started Enolytics in order to “fill the gap we saw between the abundance of data that was increasingly available within the wine and spirits industry, and the lack of cogent analytics of that data. At the time, I thought that the wine industry in particular was unique in how far behind the curve of data science it was.”
Except we aren’t unique in this, as I realized while reading and reviewing this book. (You’re welcome to check out the article here. It’s free to register if you aren’t already.) Not only is the wine industry far from alone in being behind the curve, but the curve itself is still being defined.
This is where it gets interesting. With the relationship between wine, spirits, data and analytics still being defined, the potential and possibilities are in front of us. And they’re fascinating, because we don’t have to be limited or hemmed in by long-established ways of doing things.
Which is a really great thing, since the long-established ways of doing things in the industry could use some fresh blood.
For us, that means a whole mind map of connections between systems architecture, AI, enhanced segmentation, forecasting and predictive analysis.
For you, it can mean using data to benefit your business.
We’ll take care of the data science. You take care of your customers.
Let’s get started.
I look forward to hearing from you, and thank you as always for reading.
Cathy