Data Science can seem like a nebulous concept and an omniscient presence in our day to day lives. It's a buzzword that the Average Jane could recognize but couldn't explain it's meaning. Defining Data Science in it of itself is a topic all on it's own. So why would anyone choose Data Science as their career path without knowing what it truly means to be a Data Scientist?
What is Data Science?
Data Science is the intake of information, cleaning, scrubbing, rearranging, and formatting it into a usable structure for answering questions about a data set. When given information about a subject, a data scientist is able to take that information, transform it, and present it in some meaningful way to satisfy aa given question.
Consider this: Data Scientists exist wherever data exists. Always. On a marketing team analyzing trends and making prediction for the future, taking in crime statistics for officers to be aware of which places are statistically "higher risk" and how to find out why that it, or as simple as working for Walmart to predict what items will sell well and how much to stock based on past trends of similar items. In the most general sense, that is what a data scientist does.
Why Data Science is important to me
I'm an avid gamer. I like to spend my free time playing a videogame, backwards and forwards, exploring every detail and making multiply play throughs of a single game. In a strategy game, there can be a lot of statistics to keep in mind. More often then not, the numbers are overwhelming. So how does one keep track of every bit of information? The answer is: you don't. Not efficiently, anyways
Players, especially true in my case, tend to take to the internet for information and will scrub through webpage after webpage to find what they need. It's a tedious and long process but there isn't a better way to do it? Except that this is Data! We could take in the information we need, run it into an algorithm and tell it to give us only what we need? And indeed, I've already done so with the statistics of a game titled Fire Emblem: Three Houses and posted it to reddit for use users to play test and give feed back on.
The purpose of this project was simply to make an easy to use, all-in-one information sheet to save players time and energy. Information documents like this are examples of how a data scientist might reformat and cleanup data into something more useable. Writing a series of algorithms to automatically comb the information for only the desired results is just the tip of the iceberg.
Why Data Science is important to YOU?
As I've said, Data Scientist exist anywhere data does, including in your purchases. You've probably noticed that when you're window shopping on Amazon it recommends other items base on "other things people bought" and what you've looked at in the past. Now think about if you've ever bought something that was recommended to you. This is another example of Data Science in play, serving to save the end user time and effort. However, this takes things a step further in adding the extra benefit of prediction based on past examples.
That's all well and good but those are first-world solutions to a first-world problem that nobody has. What about the things that matter most like saving lives? Well, doctors and hospitals rely on data science as well. Objective and transparent data is the most valuable thing when it comes to making decision on how to move forward with new medicine. What were the effect of Medicine X patient groups 1 - 12? What were the side effects? How long where the effects? What was the mean, median, and mode of the pain ratings before and after Medicine X? These questions are critical and absolute require answers. It's a data scientist's job and privilege to give the objective truth to those who need it.
Closing Thoughts
The work data scientists do is always meant to help improve lives or, at the very least, give someone else the tools they need to do something more and improve quality of lives. This will always be relevant. This will always affect you - the reader - as long as we all live in a technical world. If there is anything I hope you take from reading this blog, may it be this: Never underestimate just how much the world revolves around math and data. It's in literally everything we do.
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