Given that data science is a relatively newer discipline (the term first referenced in 1960), there doesn’t seem to be one agreed upon answer when someone asks, “What is data science?”. The following paragraphs aren’t an attempt to come up with the perfect answer, but they will serve in a gathering of all the pieces that make up data science and why they are important. So enjoy gaining a better grasp of this universe.
The public’s understanding of data science is engrossed with buzzwords like, “Machine Learning, Programming, Artificial Intelligence, Predictive Modeling, Visualizations, etc”. Although it is true that these are important pieces within Data Science, I think people miss the simple understanding of this field of study. Data science is not about making complicated predictive machine learning models, creating impressive data visualizations, or writing code….
It’s about using data to make an impact. Data scientists do not need to touch a machine learning algorithm, run a hypothesis test, or create stunning visuals to make an impact. If you are able to solve a problem or make an insight using a source of data, no matter the method used, you are working within the realm of data science.
It didn’t take the field of data science to be created before individuals were making an impact using data. Data science is an interdisciplinary field, which is a field made up of other fields of study. Below is a great Venn Diagram that shows in a simple way where Data Science fits as a discipline.
As you can see, all the circles were already well-established fields of work. But by combining them, you get data science. We have been using mathematics to make impacts within a business for decades. It wasn’t really until big data and the internet 2.0 became part of our every day lives that we had access to such large databases of information. The data available to businesses became so robust that we needed a way to be able to access and analyze it all efficiently. By mixing in computer science and programming, we were able to accomplish this, and data science began.
A simple formula to remember:
Domain Knowledge + Mathematics + Computer Science = Data Science
It encompasses every that has to do with data. From how we collect our data, to how we analyze the data, to how we model the data, and to how we apply our data. It is a very exciting thing to be able to play detective with a set of data and uncover insights that could make a real impact within any space of work.
Hopefully, this sheds more light conceptually into what Data Science is all about.