This was a more scalable and stable form of data, but still insufficient for the amount of data we generate today. The first floppy disks were 8 inches and contained 256,256 bytes of data, about 2000 punch cards worth (and yes, it was sold in part as holding the same amount of data as a box of 2000 punch cards). It manifested in different forms including large data rolls but the most notable example was the consumer friendly floppy disk. It wasn't until the early 1980s that a new technology called magnetic storage rolled around. The punch card remained the primary form of data storage for over half a century. For certain problems, even the most basic computation makes a world of difference. It's sort of like the first time you were allowed to use a calculator on a test. Coding up data and programs through a series of holes in a piece of paper can only scale so far, but it's incredibly useful to remember it for two reasons: First, it is a great visual to keep in mind for data and second, it was revolutionary for its day because the existence of data, any data, allowed for faster and more accurate computation. The problems with this are obvious - it's manual, limited, and not to mention fragile. To get to the point where the digital world would become intertwined with almost every person's life, data had to grow. It was simply the first chapter in the origins of data science. Of course, the digitization of data isn't the whole story. But now, literally every piece of information that we want to endure has to be translated into a new form. Even after the introduction of the printing press, handwritten works were still just as valid as a resource. It's incredible to think that while it may seem hyperbolic, it's hard to find another moment in human history where there was an innovation that made all previous stored information invalid. From books to health records to government services, it's becoming increasingly challenging to find corners of society not impacted by the digital revolution. Inside, you will find countless stories of individuals, companies, and in some cases countries racing to digitize any and all information. If you really want a sense of how big this moment is in the context of what we're here to talk about, data science, just open any newspaper over the past 10 years. It's hard to find another moment in human history where there was an innovation that made all previous stored information invalid. It is because the digital elements of information have become essential. Stack them on their desk (if you can) and they'd probably run away and never come back. Or, to better replicate the scale of what we're going to talk about, entire libraries of thick books, overflowing with tables of information. Hand them a table scrawled on a wrinkly piece of paper. Go ask a data scientist to work on something that isn't digitized. In recent years, digital information has gotten so pervasive and essential that we've almost become unwilling to handle anything that isn't in a digital form. These digital letters are actually a systematic collection of ones and zeros that encodes to pixels in various hues and at a specific density. The words you are reading on your computer screen are an example of this. In the context of data science, the only form of data that matters is digital data.ĭigital data is information that is not easily interpreted by an individual but instead relies on machines to interpret, process, and alter it. What makes something count as data? Is a handwritten ledger from the year 1500 considered data? Is a book sitting on a store shelf data? Are we all just data? We've gone so far as to personify data in everyday conversation. It has become ubiquitous, even more so for people who work in tech. It’s hard to imagine a world before data. And the folks that are using it are already reaping the benefits… Data science, when applied to different fields can lead to incredible new insights. In reality, data science is evolving so fast and has already shown such enormous range of possibility that a wider definition is essential to understanding it.Īnd while it's hard to pin down a specific definition, it's quite easy to see and feel its impact. Like any new field, it's often tempting but counterproductive to try to put concrete bounds on its definition. Everyone is talking about it, a lot are claiming to do it, and increasingly, more people are hiring for it.ĭata science, in its most basic terms, can be defined as obtaining insights and information, really anything of value, out of data. It's certainly something that seems to be on people's minds lately. More and more, data science is finding a way into our businesses, our communities, and in some cases, our lives.
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