Data science is a field that has driven our lives for a very long time now. It is the process of how we think, how we behave, and how we examine things to a particular scope. It influences various regular stuff in our lives, whether with our thinking, common sense, statistical thought, technological advances, and many more.
While that is a comprehensive spectrum of things, we must first recognize what data science is. What’s the definition of data science? Where did it originate? Why is it there? How does it work? Let us take a look at data science in all its glory.
What is Data Science?
Data science is a field of study. That’s right. It isn’t a specific thing, nor is it a single object wherein you can focus on one aspect only. Instead, it is a collection of processes, algorithms, methods, and systems to gain knowledge for the use of other specific fields.
In a nutshell, we can imagine that data science involves the scientific method of thinking. It also involves statistical techniques that we use to arrive at conclusions, the computer processing and engineering that we practice developing reasonable automated processes and artificial intelligence, and other innovative technologies that help shape our future learning and understanding of the world.
It is in the two words itself, data and science. It is the science of gaining data – information that we need to reach the best possible conclusions. Once we conclude, then we can make ways on how to improve our overall quality of life.
In short, it is the way we collect data. It is the rule on how we acquire additional knowledge on a particular anything. There is no way to shrink it down, for it is a broad interdisciplinary field on its own.
What is Data?
Data is the tiny little bits of visual information that we get from different kinds of sources. It is the culmination of the things that we try to find an answer to. It is the pieces that compose our general information.
Therefore, even though we do not notice it, we collect data every single day of our lives.
Where did Data Science Start?
Data science started with the first humans that walked the Earth. If you were to go back in time, that would probably be somewhere in Africa. Early humans, unaware that they were gaining a more complex type of thinking, perhaps because they haven’t dived that deep into science just yet.
Why is Data Science so Important?
Since time immemorial, data science has been used to advance our collective technologies and knowledge further. It has been at the forefront of everything that we’re doing. Each person desires to gain understanding; even more, each individual has a desire for proof.
What do we mean by this? People believe only after what they have seen. They don’t believe in falsehood, and academicians in the past (bar the alleged sorcerers and those believing in witchcraft) often looked for concrete evidence on the things that are present in reality.
Therefore, we can assume that data science was already present, even though the term hasn’t been coined in its time yet. The dawn of the Hellenistic age gave rise to this challenging course of thinking, and from there, the rest is history.
Data science is essential since, without it, we have nothing. Again, it is the way we think about things. Our discovery of fire is made through a scientific method of thinking. After probably seeing something burn because of lightning, we arrived at a hypothesis, experimented with it, and had success discovering it. One can argue that it was evolution at work, but on the other hand, without the experimentation, our progress would’ve been much slower.
As you can imagine, without data science, the human race will pretty much stay in the Stone Age. We didn’t see data science working back then.
Who coined the term Data Science?
As much as it had already existed from ancient times, data science was only coined very recently. It was coined when technologies were becoming more and more advanced and sophisticated. It was John Tukey, an American mathematician that first coined the term “data analysis.” This is the first time the term data science, or at least a term analogous to it, was introduced. Then, as time went by, it became more and more popular, eventually culminating in its prominence in modern times.
However, as you can see from how we defined data science above, there is still no proper definition for data science after all this time. It’s considered to be a pseudo-term as of the moment, a placeholder term of sorts.
Whichever definition they decide to come up with, it’s sure that the words data science will remain relevant until the future.
What happens in Data Science?
Data science is more like a process. Still, it is a collective science that encompasses different fields simply because it deals with data. Therefore, to fully and logically take the best approach to data science, we must see that it is a train of thought in the simplest sense.
However, several methods have already been developed on the onset of more recent technologies. These methods are primarily used in statistics, as data is heavily dependent on statistics. Data science has also been used in Machine Learning, to which it worked wonders since computers process data faster than a man would ever do.
Because of its vast spectrum, data science has brought forth different disciplines and models, including clustering, dimensionality reduction, decision tree, linear regression, logistic regression, and Support Vector Machine (SVM).
In short, everything that has something to do with the organization, implementation, and recognition of data in different kinds of mediums.
How does Data Science help?
Data science helps by keeping data organized and recognizable on a large scale. While it was mainly used in small things in the past, today’s technology can permit us to learn almost anything from the touch of a fingertip. With that kind of data volume, we can easily see why data science is crucial for your everyday big corporation.
Data science is a helpful tool as businesses increase their inventories and more highly sensitive discoveries to fluctuations and errors. Indeed, data is everywhere nowadays. The proof that people were craving in the past is now in the form of letters and numbers. These data are the ultimate parameters for evidence now.
Remember, it is with a reason that numbers and data are looked for when talking about academic studies and scientific discoveries. If the data adds up, then it must be true!
Data Science versus Information Science
The last on the list that we’re going to discuss is information science. These two fields are often confused by one another. Indeed, they are too similar to each other. If a newbie in the field of sciences were to be asked about their difference, one would probably say they don’t differ that much.
However, you can easily distinguish from each other by identifying information and data. In a nutshell, data are pieces of information, while information is, well, a culmination of data. In short, information science deals with the scientific organization of information. This includes library records and such. It is an umbrella science for data science, but in reality, it also isn’t. You can differentiate Data science simply by looking at modern technologies. Data in servers across the globe cannot be defined as information and vice versa.
Therefore, there’s a thin line that one needs to tread carefully to understand what they’re talking about when data science is brought up.
Data science is a broad science to talk about. It deals with our thinking, our methods, and the processes that we use for the efficient flow of our modern-day technologies. Data is crucial in giving us insight into what went wrong and what’s correct and plausible. When we talk about information, we usually think about our smartphones and the internet connection we use in our daily lives.
Data has indeed rooted itself in society in the past recent years. Although it wasn’t in its digital form in ancient times, it has certainly shown itself to everybody as humans progressed in different kinds and types of sciences. Computers are a miracle to have, and it’s pretty bothering though that our civilization only advances drastically through wars of epic proportions. That’s another topic on its own, though.
Data science is an essential aspect of humanity. Without data flow, there isn’t anything much to do other than relying on lady luck itself.