Discovering Knowledge Hidden in Big Data From Machine-Learning Techniques

Discovering Knowledge Hidden in Big Data From Machine-Learning Techniques

Adiraju Prashantha Rao (Anurag Group of Institutions, India)
Copyright: © 2019 |Pages: 17
DOI: 10.4018/978-1-5225-7501-6.ch037
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As the speed of information growth exceeds in this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. Data analytic is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is about discovering knowledge from large volumes data and applying it to the business. Machine learning is ideal for exploiting the opportunities hidden in big data. This chapter able to discover and display the patterns buried in the data using machine learning.
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Big Data Applications

Patient Data Sensing and Clinical Records

Initially, supporting increasing potential patients in hospitals or care centers requires remote monitoring of patients as a solution, which in turn leads to difficulty in handling challenges of big data i.e. volume, velocity, variety, veracity etc. Also the full cycle of this huge data (i.e. capturing, gathering, clearing, transforming, formats, storing, analyzing and visualizing) for some patients should be covered in real time. Another data source that caters for data diversity and variety is the patient’s clinical records. In all cases, data is made available for access, for all teams of doctors, nurses, administrators and social agents. So the technologies other than Hadoop like batch processing should be considered as better solutions.

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