For the first time in computing history, it’s possible for machines to learn from experience and penetrate the complexity of data to identify associations. The field is called cognitive analyticsTM —inspired by how the human brain processes information, draws conclusions, and codifies instincts and experience into learning.
Instead of depending on predefined rules and structured queries to uncover answers, cognitive analytics relies on technology systems to generate hypotheses, drawing from a wide variety of potentially relevant information and connections. Unlike in traditional analysis, the more data fed to a machine learning system, the more it can learn, resulting in higher-quality insights.
Cognitive analytics can push past the limitations of human cognition, allowing us to process and understand big data in real time, undaunted by exploding volumes of data or wild fluctuations in form, structure, and quality. For organizations that want to improve their ability to sense and respond, cognitive analytics offers a powerful way to bridge the gap between the promise of big data and the reality of practical decision making.
Rajeev Ronanki, principal, Deloitte Consulting LLP, shares an example of how a national healthcare plan applied cognitive analytics to gain new insights, helping to improve the efficiency and accuracy of their predictions.
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