Running head: BIG DATA, DATA MINING ASPECTS, AND INFORMATICS IN NURSING 1
Big Data, Data Mining Aspects, and Informatics in Nursing
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Date: BIG DATA, DATA MINING ASPECTS, AND INFORMATICS IN NURSING
2
Introduction
From a medical perspective, data collection and data mining play a critical in maintaining
useful patient information and more convenient access and extraction. A large amount of data is referred to as big data, while the process of extracting that data through various patens is data mining. The method of data collection, analyzing, and leveraging patient's physical and clinical data is referred to as big data. Big data is often processed using machine learning algorithms or a computer. The data collection and mining is critical in data mining is essential in the concept of continuity planning in instances such as disaster management. All these activities incorporate the
use of advanced technology that is vital in healthcare education. The information that is derived from big data helps the physicians and the healthcare management to prescribe treatment and make the right decisions with higher accuracy (Chu, 2014). Through the use of technical data that is available, it helps in eliminating guesswork while
administering medication and lower cost as well as enhances patients care. Data mining is where extensive data set is analyzed, and patterns discovered and used to predict the possibility of events that might happen in the future (Chu, 2014). The paper will focus on the aspect of big data
and data mining and the value it has to the healthcare, and describe the concept of continuity planning. Also, the paper will locate and discuss a healthcare article that highlights the benefits and drawbacks of using healthcare education technology. Aspects of Big Data and Data Mining
One point of big data and data mining is the sorting and storing the most critical data from vast volumes of data storage in a database and categorizing it; this concept of data storage and sorting information in a database helps healthcare to avoid duplication. Value is brought to
Big Data, Data Mining Aspects, and Informatics in Nursing
Name:
Institution Affiliate:
Course:
Date: BIG DATA, DATA MINING ASPECTS, AND INFORMATICS IN NURSING
2
Introduction
From a medical perspective, data collection and data mining play a critical in maintaining
useful patient information and more convenient access and extraction. A large amount of data is referred to as big data, while the process of extracting that data through various patens is data mining. The method of data collection, analyzing, and leveraging patient's physical and clinical data is referred to as big data. Big data is often processed using machine learning algorithms or a computer. The data collection and mining is critical in data mining is essential in the concept of continuity planning in instances such as disaster management. All these activities incorporate the
use of advanced technology that is vital in healthcare education. The information that is derived from big data helps the physicians and the healthcare management to prescribe treatment and make the right decisions with higher accuracy (Chu, 2014). Through the use of technical data that is available, it helps in eliminating guesswork while
administering medication and lower cost as well as enhances patients care. Data mining is where extensive data set is analyzed, and patterns discovered and used to predict the possibility of events that might happen in the future (Chu, 2014). The paper will focus on the aspect of big data
and data mining and the value it has to the healthcare, and describe the concept of continuity planning. Also, the paper will locate and discuss a healthcare article that highlights the benefits and drawbacks of using healthcare education technology. Aspects of Big Data and Data Mining
One point of big data and data mining is the sorting and storing the most critical data from vast volumes of data storage in a database and categorizing it; this concept of data storage and sorting information in a database helps healthcare to avoid duplication. Value is brought to
