What's So Exciting About Data Science?August 22nd, 2017 in User Stories
Data Science is a rapidly evolving and exciting field. But don’t take our word for it! DataCamp asked 11 data science professionals and enthusiasts about why they are so excited about data science. Here's what they said.
“For me, data science was a way to become a detective.”
For me, data science was a way to become a detective. For every new case, you have to go into a new field to try to understand how it works, to massage the data until you understand them, to try to acquire all the knowledge of the field without being a specialist. And because I am very curious about very different techniques in science, for me, it is exactly what I wanted.
Do you know the show Columbo, the old show from the 80s? Columbo was a private detective, and in every episode he was in a different profession and he had to solve a case. And he did it by investigating the profession. It could be the military, Hollywood, whatever. And every time he had to very quickly understand the implicit knowledge in the field. He had to talk to people, understand how they thought, stuff like that. And I feel a bit like that with data science. When you are data scientist, you spend a lot of time, or at least I do, talking with specialists of the field and very often they have a lot of implicit knowledge.
For example, in my company, we are doing a bit of IoT (Internet of Things) and are working in the Champagne region with a company that is trying to connect the tanks that hold the alcohol. So we put sensors on these tanks and collected data from them to understand how to improve the process of champagne production. And in order to improve, you need the data. And in order to treat the data, we need to understand how champagne is made. And it is really fun, because if you talk to anyone from the engineers to the growers to any employee in the place, they all have some knowledge. They all know a bit of stuff that they kind of don’t share with everyone. And we have to try extract that by talking to them, by understanding, by also making some comparisons with previous projects we’ve worked on. And it is really fun to do that.
“The excitement in data science is in the journey toward achieving three significant kinds of results: discovery, insights, and innovation.”
For me, the excitement in data science is in the journey toward achieving three significant kinds of results: discovery, insights, and innovation. As a lifelong scientist, I was always doing data analysis, mostly using standard methods. But when I first encountered mathematically interesting algorithms that can be used to explore large data sets in novel ways to achieve novel results, I was hooked and then decided to dive into data science as my career.
“Data science is the future, and it is better to be on the cutting-edge than left behind.”
I think data science is the future of data. Data science is the future of applied econometrics, I would definitely say…[At my last job], we did a lot of public evaluation but it was not formal. Data science, in my opinion, is the future of this kind of work. It is the only way to do it efficiently, replicably, and get great results. You have a lot more tools and a lot more flexibility in the way you can collect data, the way you can exploit multiple databases all at once, and produce something really usable as well. Data science is the future, and it is better to be on the cutting-edge than left behind.
“Data Scientists and Machine Learning Engineers are in great demand and at the forefront of coming AI revolution”
Big Data is enabling Data Science and Machine Learning to change our world in amazing ways, at least as much as the industrial revolution. Data Scientists and Machine Learning Engineers are in great demand and at the forefront of coming AI revolution, from making new life-saving medicines to self-driving cars to annoyingly personalized ads.
However Big Data also has negative effects, such as reducing privacy and to address it I propose a "Golden Rule of Data Mining": Don't do data mining on someone else's data if you don't want it done on your data.
“Data science makes me feel powerful!”
Data science makes me feel powerful! There are basically two reasons for my saying that.
One is the fact that data science is a rapidly evolving area, so that a large part of a data scientist's work, at least as I envision it, is updating his or her methods, tools, and workflows. I really like that my work is evolving with the progress of data science, so that I never get bored.
Also, I like to think that with the growing amount of data available to analyze, using and designing new tools to gain efficiency is a crucial part of the job. And of course, I find learning about and using such tools particularly rewarding—I'm French, so I like to not work too much! Joking aside, and to give you an example, I discovered ggplot and dplyr not so long ago, and it is really helping me work more efficiently in the long run.
“Being able to obtain, process, and build models out of data, which will ultimately be used for their predictive capabilities [...] is incredibly exciting in my view”
Though "data science" refers to a varied set of somewhat related tasks and processes, my favorite are those concerning prediction. One of the defining characteristics of humans is our ability to take in available data and use it to make predictions, however certain or uncertain, about the future, however distant or near. Being able to obtain, process, and build models out of data, which will ultimately be used for their predictive capabilities -- be it for health care, financial decisions, customer service, or baseball outcomes -- is incredibly exciting in my view. This predictive capability, to me, is both the core of humanity and the core of data science, and the simple beauty of this parallel is far too often overlooked.
“Data science is our means of taming unstructured information and gathering insight.”
It's an exciting time to be alive, because there is more data available than ever before. There is more data than we could ever analyze, much less understand. In that context, data science is our means of taming unstructured information and gathering insight. I'm a cultural sociologist and learning data science is important to me because people upload tons of text that may tell us about their worldviews and their values, if only we know how to analyze it.
“Data scientists help improve how humans make decisions and how algorithms optimize outcomes”
I believe that data science has the power to improve the human condition by helping us investigate phenomena, acquire new knowledge and integrate previous knowledge with new ideas. Through the collection, analysis and interpretation of data, data scientists help improve how humans make decisions and how algorithms optimize outcomes. We have already seen how companies are the tools and methods of data science to improve how we diagnose cancer, fight global warming and more.
“I'm excited to think about a future where data-driven decisions become more and more commonplace all around the world.”
For me, the thing about data science that makes it so exciting to the modern world is its unparalleled ubiquity—data science is everywhere. It is ultimately just a set of skills derived from computer science and mathematics, and this set of skills can be universally applied to learn from the past and improve future performances in any discipline you can think of. That's what makes data science so relevant: its enormous scope and potential to improve life across a wide variety of sectors. I'm excited to think about a future where data-driven decisions become more and more commonplace all around the world.
“Data science allows me to try various ideas using scientific methods”
Data science allows me to try various ideas using scientific methods. Moreover, I have always liked working on math problems but find doing so in a theoretical fashion somehow limiting. Applying mathematical reasoning to real-world problems is very satisfying. Finally, the data science field is growing rapidly and there is always new things to learn. This is something that I enjoy a lot as well: learning new content and sharing my knowledge with others.
“One of the things that makes data science so interesting is how fast it’s evolving”
One of the things that makes data science so interesting is how fast it’s evolving. But you’ve got to keep learning to keep up. If you’re not, you’re falling behind.
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