Course: Information Technology in a Global Economy Part A: Discussion 7 (Week 6): Big Data The rising importance of big-data computing stems from advances in many different technologies. Some of thes
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Post 1:
Discussion 7 (Week 6): Big Data
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Cloud computing facilities play an important role in global computing and big data rather than any other technologies these days as it offers “pay as you go”, a payment method for cloud computing that charges based on usage. Cloud computing infrastructures offer an effective support for addressing both the computational and data storage needs of big data mining applications. In fact, complex data mining tasks involve data- and compute-intensive algorithms that require large and efficient storage facilities together with high performance processors to get results in acceptable times. (Catlett, 2013) This explains the services offered by cloud computing in regards to big data in infrastructure perspective and its development as well.
Cloud services like AWS, Azure, VMware and Google cloud were the examples that we come across these days and enterprise perspective which offer more job opportunities to the consultants and full-time employees which on other end impacts the global economy as well. Cloud computing systems today are used for implementing dynamic data centers and for high-performance computing on massive number of processors. They can also be effectively used as scalable infrastructures for running big data analysis that often involve large data sets and complex algorithms. Thus, Clouds can be platforms for the implementation and delivery of scalable service-oriented knowledge discovery applications. (Catlett, 2013)
Reference:
Catlett, C. (2013). Cloud Computing and Big Data. IOS Press.
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Post 2:
Discussion 7
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According to the article research, Data storage is a fundamental process in the big data era, considering whether the raw data collected will put for use—the information collected in healthcare characterized by a complex process governed by stringent regulations. For instance, the healthcare providers collect data from various sources, such as patient intake forms, treatment evaluation, and consent forms, among others (Rolim, Koch, Westphall, Werner, Fracalossi, & Salvador, 2010). Data storage is done primarily through manual entry, an aspect that exposes it to errors, and inaccurate entries, an element that can ultimately undermine the quality of the data. The mistakes and inability to authenticate the quality of the data collected are challenging that the various health facilities must persevere (Schobel, Probst, Reichert, Schickler, & Pryss, 2019). Besides, in the healthcare facilities where digitization of records done, the health data is prone to intrusion and compromised by hackers, considering that most facilities lack resilient information security systems.
Data storage is a systematic process that entails gathering, analyzing, and interpreting various types of information obtained from different sources, which helps ensure that the health facilities have much-needed information for decision making (Rolim et al., 2010). In my opinion, data collected about the patients can be used by the administration of healthcare to improve their decision-making. As I work for healthcare, I know the importance of data and how the analytics developed out of the data. However, these aspects can ultimately enhance issues, such as the facilities' marketing campaign. Electronic health records' predictive capabilities also improved through Data storage, which ensures that better health outcomes can give to the patients (Schobel et al., 2019). Besides, Data storage paves the way for the development of technological gadgets, such as wearable diagnostics, which improves the wealth of the patients, by tracking their vitals in real-time.
Reference
Tao, H., Bhuiyan, M. Z. A., Abdalla, A. N., Hassan, M. M., Zain, J. M., & Hayajneh, T. (2018). Secured Data storage with hardware-based ciphers for IoT-based healthcare. IEEE Internet of Things Journal, 6(1), 410-420.
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