Homework answers / question archive / Running head: DATA GATHERING IN HEALTHCARE 1 Discussion 1 Data Storage and Integration In E-Health Industry The modern-day e-healthcare industry collects massive amounts of data from numerous sources such as lab results, research, patients' records, and medical history

Running head: DATA GATHERING IN HEALTHCARE 1 Discussion 1 Data Storage and Integration In E-Health Industry The modern-day e-healthcare industry collects massive amounts of data from numerous sources such as lab results, research, patients' records, and medical history

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Running head: DATA GATHERING IN HEALTHCARE 1 Discussion 1 Data Storage and Integration In E-Health Industry The modern-day e-healthcare industry collects massive amounts of data from numerous sources such as lab results, research, patients' records, and medical history. One of the biggest problems that the firm must solve is infrastructure challenges. One of the notable benefits of storing massive amounts of data is that they enhance the ability for e-healthcare organizations to engage in analytical tasks and improve their functionality based on the insights generated. For instance, e-healthcare relies on the insights generated through analytics to improve customer care services, management of patients within the firm, and implement personalized treatment (Dash et al., 2019). Big data integration plays an essential role in enhancing the management of big data within the firm. For instance, data syncing helps to create a single version of high-quality data for analytical purposes. The massive amounts of data need a place to rest, meaning that these organizations must invest in massive amounts of storage space. In other words, e-healthcare institutions must invest in high-tech servers of cloud resources to ensure they have sufficient computing resources. Another significant challenge is ensuring the security of the data and safeguarding it from unauthorized access (Larry). There are numerous ways in which organizations can secure their data against unauthorized access, and one of the typical techniques involves the use of techniques such as access control measures, cryptographic techniques, or reliance on third parties. E-healthcare organizations must also ensure that they install scalable data storage systems that will help them to work with a fluctuating workload. Handling big data is a very challenging task, and some of the significant tasks associated with data integration in the e-healthcare industry include syncing across data sources, managing the data as one big data structure, and the uncertainty of data management. The uncertainty in data management is brought about by the availability and use of an extensive range of innovative data management tools and frameworks that are designed to enhance operational and analytical processing. However, despite the availability of numerous big data management skills, there is a significant shortage of skilled human resources such as data analysts and data scientists who can DATA GATHERING IN HEALTHCARE 2 oversee the execution of such tasks (Kadadi et al., 2014). e-healthcare organizations source their big data from numerous different sources, meaning that it is challenging to sync all the data from the different sources. References Dash, S., Shakyawar, S.K., Sharma, M., Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data 6, 54. http://doi.org/10.1186/s40537019-0217-0 Kadadi, A., Agrawal, R., Nyamful, C., & Atiq, R. (2014, October). Challenges of data integration and interoperability in big data. In 2014 IEEE international conference on big data (big data) (pp. 38-40). IEEE. Larry Alton. The 7 Biggest Problems in Data Storage – and How to Overcome Them. Retrieved from https://www.smartdatacollective.com/7-biggest-problems-data-storage-overcome/ Discussion 2 Data analysis is one of the parts of Big Data Analytics which is now the new trend that is getting used in mostly all the sectors of the work. The investment of this theory is found evidently in the healthcare industry as well. The e-healthcare industry is the most used in this present scenario and thus deals in a huge amount of data each day (Dai, Wang, Xu, Wan, & Imran, 2019). The benefits that this industry faces from the implementation of the data analysis are huge. It helps in improved operational efficiency. This data analysis helps in studying the historical admission and the rate of the discharge of the patients of the healthcare industry. The tool helps in handling the huge data easily and to keep track properly. The involvement of these techniques helps in controlling the cost of the operations. The data analysis helps in providing advanced patients care and treatment. It helps in controlling the health records of the patients as well as regulating their tests and treatment data (Dai, Wang, Xu, Wan, & Imran, 2019). The technique helps in discovering the cure and the disease of the patients at the right time. This would help in diagnosing the disease quickly and getting the treatment DATA GATHERING IN HEALTHCARE easily. This helps in providing the ideas of the hidden patterns and the analyzing of the large data. As this technique helps in providing the benefits it also experiences several challenges. The e-healthcare industry is the section which deals with a huge data of confidential information. This information would help in maintaining the privacy of the patients (Das & Mohapatro, 2014). The challenges could be the handling of the privacy and the security of those data. It is often found that the data of the confidential information are not managed properly resulting in the loss of those. This however made the functioning of the system stop. The data analysis fails to provide data retention. The health care data requires having a retention period of at least 5 years. This fewer retention results in the hampering of the functioning of the healthcare system. References Dai, H.-N., Wang, H., Xu, G., Wan, J., & Imran, M. (2019). Big Data Analytics for Manufacturing Internet of Things: Opportunities. Challenges and Enabling Technologies, 14. Das, T., & Mohapatro, A. (2014). A study on big data integration with data warehouse. International Journal of Computer Trends and Technology, 9(4), 188192. 3