From the way the media describes it, machine learning algorithms were just invented last week and data was never “big” until Google came along. There’s a distinct lack of respect for the researchers in academia and industry labs who have been working on this kind of stuff for years, and whose work is based on decades (in some cases, centuries) of work by statisticians, computer scientists, mathematicians, engineers, and scientists of all types.

What is “Big Data” anyway? What does “data science” mean? What is the relationship between Big Data and data science? Is data science the science of Big Data? Is data science only the stuff going on in companies like Google and Facebook and tech companies? Why do many people refer to Big Data as crossing disciplines (astronomy, finance, tech, etc.) and to data science as only taking place in tech? Just how big is big? Or is it just a relative term? These terms are so ambiguous, they’re well-nigh meaningless. There’s a lack of definitions around the most basic terminology. So, what is eyebrow-raising about Big Data and data science? Let’s count the ways: If you’re a skeptic too, it probably means you have something useful to contribute to making data science into a more legitimate field that has the power to have a positive impact on society. We want to address this up front to let you know: we’re right there with you. Let’s get this out of the way right off the bat, because many of you are likely skeptical of data science already for many of the reasons we were. After that we’ll explain what made us get past our own concerns, to the point where Rachel created a course on data science at Columbia University, Cathy blogged the course, and you’re now reading a book based on it. Instead of ignoring it, we decided to explore it more.īut before we go into that, let’s first delve into what struck us as confusing and vague-perhaps you’ve had similar inclinations. Perhaps, we considered, it’s even a paradigm shift that plays to our strengths. But we couldn’t get rid of a nagging feeling that there was something real there, perhaps something deep and profound representing a paradigm shift in our culture around data. Over the past few years, there’s been a lot of hype in the media about “data science” and “Big Data.” A reasonable first reaction to all of this might be some combination of skepticism and confusion indeed we, Cathy and Rachel, had that exact reaction.Īnd we let ourselves indulge in our bewilderment for a while, first separately, and then, once we met, together over many Wednesday morning breakfasts.

Data science basics ppt