By Rob Thomas, IBM Analytics For decades, data and analytics have played an important role in our economy. The process of analyzing data, however, remains labor intensive. Even with the most advanced techniques, data scientists spend countless hours developing, testing and retooling analytic models one step at a time. Worse yet, most organizations cannot find enough data scientists to complete this labor-intensive work. The impact is that we have not yet fully realized the promise of continuous intelligence; until now. The field of machine learning promises to streamline the application of analytics and create a new era of autonomous data. Instead of simply helping data scientists crunch the numbers, organizations will use machine learning to automatically understand and learn from data. The result will move us from the current state of predictive analytics, where organizations guess what will happen next, to cognitive business, where organizations develop a deep understanding of markets based on continuously updated data. Think about the possibilities with continuous intelligence. Cars will not simply drive themselves; they will know where you want to go next. Grocery stores will not just cross-promote products; they will fill your cart before you enter the store. Doctors will not just write prescriptions; they will create holistic health plans based on data constantly updated from activity trackers, eating patterns and medical tests. So how does machine learning make this possible?
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