From gigantic, room-filling computers to personal computers, and then to the web, mobile devices, cloud computing and the Internet of Things (IoT)—the technology used to transmit data evolves almost as quickly as data is created. The 'big' in big data is an understatement—data pours in at an unprecedented rate, at any given moment in time, in all kinds of structured and unstructured formats.
Emails, text messages, social media, documents, mobile apps and a number of other channels are giving big data analysts more datasets to study than ever before. With the amount of data available to analyze today, businesses can glean better insights into customer behavior and use predictive analytics to drive business strategies; the problem is, many businesses are not tapping into the full potential of big data due to a lack of talent to analyze it. According to Forrester, companies only analyzed about 12% of the data available to them, leaving the other 88% on the cutting room floor.
The future of big data lies in predictive analytics, cognitive machines, and the strong demand for more data analysts to find the value in the data that is often cast aside. Take a closer look at some of the leading big data industry and career trends below:
Predictive Analytics for Business
Now an integral part of data analytics platforms, predictive analytics are used to shed light on overlooked trends and patterns. Predictive analytics offer insight on target markets, customers and businesses to help analysts make more accurate predictions and shape better business outcomes.
Predictive analytics will be especially helpful in industries such as healthcare, where accurate predictions through health informatics can improve patient health and cut down healthcare costs. PinnacleHealth, for example, had success using IBM Cognos Business Intelligence to predict the risk of chronic obstructive pulmonary disease (COPD) patient readmissions, and thus intervened with at-risk patients to cut costs and improve patient outcomes.
Predictive analytics and predictive analytics tools will continue to open up opportunities for analysts to uncover business opportunities, anticipate and prevent problems and ultimately improve business decision-making.
Cognitive Machine Improvements
The relationship between humans and machines is becoming stronger with the improved ability for machines to learn and 'remember.' Cognitive computing is a buzzword for 2016, and it’s revolutionizing the business landscape by giving machines more human-like qualities to learn from previous data and improve future outcomes. As cognitive computing abilities improve, machines will be able to take over more human labor with fewer errors and the ability to complete work at breakneck speed.
IBM’s Watson supercomputer, for example, is leading the cognitive machine revolution by using natural language to quickly analyze unstructured data and provide answers to complex questions.
Big Data Career Growth
Big data analytics remains one of the top priorities for organizations to improve performance, but a lack of available talent continues to plague employers. With median salaries that average in the six-figure range, the demand for more big data analysts to exploit the power of big data will increase substantially as more and more data becomes available. The rising demand for more analytical talent is also driving many universities to expand big data degree programs. A big data analytics degree is essential for the next generation of big data experts, as it gives them the skills necessary to thrive in the changing industry.
Whether it’s using predictive analytics to change the world for the better, or developing machines to ease human labor, big data has huge opportunities for the future. Human insight will always reign supreme, but with the help of big data, human insight accuracy can improve significantly.