What is Predictive Analytics?
Webopedia defines predictive analytics as “the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends.” While predictive analytics can tell you more than descriptive analytics, it is not a crystal ball for the future. Patterns do not always hold true; however, this form of analytics can move the process of analyzing data from the hindsight of descriptive analytics, past insight into current data sets, and into the beginning stages of foresight.
Uses for Predictive Analytics Today
Predictive analytics are used for a variety of tasks today. Some tout predictive analytics as the bridge between artificial intelligence and mechanical learning. It’s also being used as a boom for those in the health industry. Furthermore, governments can use predictive analytics to respond to public needs, inform during elections, and respond to new and unfolding urban issues that are unprecedented. Analyzing big data with predictive analytics has few limits but many potential uses.
Benefits and Challenges of Predictive Analytics
Applying predictive analytics to historical data set allows government entities and research professionals to determine trends that better inform and shape public policy. Using data improves the strength of policies, positively shapes customer experiences, and can shape technology in incredible ways. However, predictive analytics has challenges as well. For example, any analysis is only as strong as the data set it’s analyzing. Predictive analytics are limited — while they can inform us of possible future trends, those trends are limited to populations. This especially becomes an issue when dealing with healthcare. When dealing with data sets that involve an entire population, predictive analytics can be beneficial. However, it’s often unhelpful for dealing with single individuals.
Predictive analytics will likely become more commonplace. As artificial intelligence emerges and becomes more useful, so will predictive analytics. In addition, as the need for dealing with larger data sets rises, researchers, governments, and companies will find predictive analytics increasingly necessary. For more information on the topic, please contact us.