One of the biggest, and most interesting, uses for Big Data comes with the ability to design predictive algorithms. Whether it's a simple regression model or a fully-fledged machine learning algorithm, there is an extraordinary amount of potential in the field to create something new and useful. Essentially, being able to design a predictive model gives people the tools to approach a problem from a completely different perspective. Instead of using guesswork and one's "gut feeling" to make decisions, they can use hard data to figure out what the best course of action likely is. These algorithms are in no way guaranteed to be correct, but they do offer a higher likelihood of success than any previous methods did.
One of the best examples of the potential for predictive analysis comes with Health Care. As one article states, big data allows one to find "more opportunities to improve care" for sick health care patients, and eventually systems will be built that can provide useful care all by themselves, without issue. While this may sound like a basic generality, the meaning behind it is much more. Using Big Data, medical staffs the world over can predict who is at risk for certain diseases, what the likelihood is of a patient not taking their medicine, and even the different pre-emptive care options a patient could need. While the timeline for this to become reality is very foggy, the fact is that when it does, it could revolutionize the way we as a society approach health care. Already, IBM's Watson supercomputer is being used to help improve detection of bleeding in the brain or head trauma. Within time, it'll possible for any person to both better understand their health and how to improve it to an extent inconceivable 20 years ago.
Even in other less vital industries, predictive analytics have the potential to be a game-changer. In sports, they've already helped teams better rest players to avoid potential injuries. Traders can use it to better predict the market, and let their trading systems make profits off split-second expected movements. Sociologists can combine it with their own understanding of a certain culture or society to predict when and where issues could manifest. It's hard to over-emphasize the impact this field could have over the next few decades, as almost every industry could use it to both better understand their current state and predict where they could be down the line. As long as data continues to be plentiful and advances in AI and computing continue, there's no doubt that the future of predictive analytics remains bright.