As someone who is trying to upskill from a statistician into a data scientist, I have found the vast array of different courses and resources for learning to be daunting. Almost every university is now offering some kind of data science program (that usually costs several thousand dollars), and online there are innumerable classes, bootcamps, MOOCs, tutorials, demonstrations and projects. Picking the right one to start with is a very difficult task in and of itself!
When we consider big data, the first question most people have is “how big does data have to be to be considered big data?” I think the best way to illustrate the potential size of big data is through a contemporary example that many people have heard about.
The recent emphasis on data and analytics might make it seem like data a relatively new thing; however, data has driven human decisions since the dawn of time. Ever since we have been able to think and plan, we have been using data to inform our decisions. The difference between then and now is the methods that we used to gather data and our ability to process it. For most of human history, we gathered data through our five senses. We made decisions based on what we saw, smelled, tasted, heard, and felt. Our brain was our only processing tool, and we relied upon past experiences to inform us of what might happen in the future.