One More Step: Java Programming and Software Engineering Fundamentals Specialization

Last week I completed Duke University’s Java Programming and Software Engineering Fundamentals Specialization via Coursera. The specialization consists of five courses starting with high-level JavaScript and HTML and dives into Java fundamentals. It took a few months of learning not only programing languages, but how to approach software engineering – a key takeaway for me. 

The title of this post starts as “One More Step:…” because, as you’ve probably heard me say (e.g. here, here), this ramp up is part of a bigger plan.

More and more I (we?) hear about creating a more comprehensive view of the customer, combining data silos, real-time campaigns, anything that includes “data science” in the description… you know, recent buzz words. Sometimes we hear these in cases were they don’t even make sense, but for most cases where these business drivers could be a reality, I believe going to the cloud is the most reasonable avenue.

I’m labeling these capabilities as “buzz words”, but they will become a core part of any business, and also a fascinating one. This is why I’m betting on the cloud for the future. And this is why I’ve prioritized strengthening my software programming (Java, Python, SQL, JavaScript) foundations. I want to better understand how the different pieces work together, what are the possibilities, and what are the limitations.

This stuff is not easy. Many leaders driving businesses today lack the technical background to shape a vision that includes the full potential of what is readily available, and those who have it are not necessarily driving business – yet. Even my team at Amazon (one of the most data-drive teams I’ve worked with) had a long way to grow in this respect.

Alison Wagonfeld, VP of Marketing for Google Cloud, published an article just last year pointing out how, still, many marketers don’t know where to start when using cloud technologies. She suggests to start by partnering with a data scientist, but not for the reason most people think about – AI, algorithms, machine learning, etc.. The suggestions comes as a data scientist worth their weight will be able to guide organizations on what silos to combine for marketing purses, how to go about it, and how to get ready to start thinking about the cool stuff.

To be candid, even with with base in SQL and JavaScript I felt a little handicapped about four years ago while taking the role of Global analytics lead at ASICS. Perhaps this was the spark that lit my current path.

Continuous education will be, most likely, a part of my life moving forward… That’s as long as I can successfully sell this time investment to my wife, and soon my kids. I love you guys!