2.5 quintillion bytes of data were created every single day back in 2018, with this number having grown since then.
I’d say this is all the reason one needs to study data science.
Data is everywhere.
But I have other reasons.
Back in 2017, after four years of teaching ESL in South Korea, I decided it was time to transition into work I felt was more aligned with the impact I wanted to have going forward.
(The priceless nature of these four years is beyond the scope of this piece, but just know, deciding to teach ESL abroad changed the trajectory of my life, and undoubtedly for the better)
After doing research, it seemed like studying software development was the best route for me, but after working through some courses I purchased from Udemy (great courses by the way) as well as Free Code Camp, I realized that gaining competence in programming would be a marathon.
That hasn’t changed.
But at that time I decided instead to double down on my skills as a writer and marketer, and so in 2018 I started freelancing.
I was pretty fortunate in that I got to help a few blockchain projects with their marketing efforts, beyond other clients I did work for.
One of the most insightful takeaways from that year was discovering how rapidly technology is evolving…
I found harmony with the concept of decentralization, as well as the practical ways in which a technology such as blockchain is — and may continue to — transform sectors worldwide.
Another takeaway was related to data.
Some of the projects I came across were focused on ensuring that consumers, Internet users, patients and more are able to maintain control over their data.
From ownership to compensation, from privacy to authentication, it became clear to me that indeed, data is the new oil. As well, the way in which many founders and developers seek to innovate in the blockchain space to come up with solid solutions for how smart contracts interact with the unstructured world. It was clear to me that it was important I keep my eye on these developments.
I suppose this brings me to what lies at the foundation of my interest in studying data science:
I am committed to learning how to be a producer — and not only a consumer — of technology, so as to not only contribute, but as well, to stay on the cutting edge of things, and data science, to me, is a vital component to the shaping of society from now and on into the future.
Can we find a handful of technological developments more vital? Could we find a handful of any developments more vital?
Machine learning. Artificial intelligence. Internet-of-Things. Prediction analytics. Recommendation engines. Cryptoeconomics. Growth marketing. Self-driving cars. Public policy formation. Investigative journalism.
And on and on.
Everywhere one looks, data science is there. Or, is on the way.
At least it seems that way to me.
I see data science, more and more, as being at the genesis of all we do as human beings.
Moreover, and perhaps somewhat related:
I am interested in understanding how to leverage data analytics with respect to digital business.
Last year, while serving as a co-founder for a personal care startup, I realized how much I lacked in the way of data analytics competence.
In a fast-paced environment — which one could make a very strong argument for this being the reality we all find ourselves in — being able to effectively collect, organize, understand, harness and respond to data is essential to success.
And although we had some wins, I know more grasp of data science would’ve been a major key for doing it bigger and better.
Also, as someone who is always looking to improve, I see studying data science as both a way to renew a love for math that I had all throughout school and to challenge myself to learn how to think like a data scientist, which combines software engineering, statistics and business acumen in a way that I think matches up well with how I observe the world.
I’m a creative at heart.
I’m always thinking of ideas that could solve this or that problem.
I’m hoping data science will equip me with the tools to discover important problems and solutions to help shape the future.
I’m eager to get involved with a project, sector or initiative that I believe in, whether in agriculture, finance, supply chain, or perhaps even healthcare.
The really good thing about developing skills in data science and programming languages like Python is that the opportunity to work on world-changing endeavors is consistently present.
And that brings me to the last reason, for now at least, and it might be the most important one:
I am concerned about how much A.I. is being integrated into our world, and yet, I find A.I. has proven to be of great use.
Artificial Intelligence is one area to which data science is connected.
Some questions I have:
How will A.I. impact income disparities over time? What about knowledge disparities? What does the future of work look like for human beings when A.I. is doing so much of the work? Can A.I. be ethical?
I see data science as important to all of these questions.
And perhaps my concern is more apparent than my excitement given the above questions…
But all in all, I’m excited for the data science journey and everything adjacent.
I’m at the beginning, and it’s a challenge.
But human beings have been learning, innovating and discovering since civilization began on the African continent.
This is also reason enough to go on this journey.
Now to work on my data science study habits.
Has anyone made a daily data scientist “workout routine?”
If so, please share. Thanks :)