Abstract:
Never before has society generated such vast amounts of data pertaining to how we communicate, interact, shop and spend our free time. For most people living in this digitally connected world, our digital companions (computers, laptops, tablets and phones) record and store vast amounts of data on our state of fitness, what we eat and the places we go. Your phone for example, just by being in your pocket can record ‘how much exercise you’ve been getting and how many stairs you have been walking up and so on’ (Katz, 2012). Every time we make a call, send a text message, email, swipe our bank or loyalty cards, we leave behind a digital ‘paper trail’ that can be used to accurately determine who you are and how you choose to live your life.
Over the past two years humans have generated more data than we had recorded in the whole of human existence prior (Shaw, 2014). This data is stored in different databases around the world, and while it is scattered and unusable to most in its raw form, ‘data analytics’ has made it possible for this raw data to be ‘mined’ (Oliver and Vayre, 2015; Osei-Bryson and Rayward-Smith, 2009; Power, 2014). Once mined, patterns can be established. These patterns can be used to successfully predict how one will live their life, down to predicting what brands one will purchase in favour of competitors.
