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Healthcare Analytics Example - Predicting Hospital Readmissions for Diabetic Patients

  Scenario: A healthcare institution seeks to decrease the frequency of hospital readmissions for patients diagnosed with diabetes. Repeated hospital stays incur significant expenses and frequently signal unfavorable patient results. The business aims to utilize big data analytics to proactively identify patients with a high likelihood of readmission and react accordingly.

Predictive Analytics Concepts

  Predictive analytics is a branch of advanced analytics that uses various statistical techniques and models to analyze current and historical data in order to make predictions about future events. Here are some key concepts and methodologies involved in predictive analytics:

Big Data Analytics

  Big Data Analytics is a complex field that involves extracting valuable information from large, diverse datasets that are too big or complex to be dealt with by traditional data-processing methods. Here are some key aspects of Big Data Analytics:

Bigdata Primer

  Definition of Big Data : Big data refers to extremely large datasets that cannot be efficiently processed, analyzed, or stored with traditional data processing tools. It's characterized by the three Vs: Volume : The sheer amount of data. Velocity : The speed at which new data is generated and needs to be processed. Variety : The different types of data (structured, unstructured, and semi-structured).