Response

  The topic I choose is Data Analysis. When it comes the big data is required to be stored is of two different Electronic Health Records (EHRs) and Electronic Medical Records (EMRs) in the health care industry. This data is mainly used by the health care client for customer service optimization. One of the biggest challenges with big data is to find an efficient way that can handle these huge loads of information. It has been made available for use and for doing an efficient analysis to gain predictive results out of it. In order to achieve this, we need to have high-end computing tools and software in place that can handle big data. This brings us to another challenge of setting up this high-end hardware and computing in a clinical environment and installing the required software to run the analysis. (Ristevski & Chen, 2018)

    Experts from different wings such as mathematics, statistics, IT, and biology need to work on the analysis to gain efficient results and this always required an external setting. The data conversion needs to happen with the help of the above-quoted tools which carry algorithms related to the data mining and Machine Learning functions which eventually spit out the knowledge the researcher use. The main advantage of such data conversion is that it enhances the data gathering, storage, analysis, and data visualization in the health care industry. The visualization tools really come in handy to display the knowledge results from data conversion that can be used to make appropriate decisions. Hadoop and Apache stark are the commonly used platforms to deal with the big data and the programming language such as python or R-programming languages are being used in building the algorithm that can convert the data gathered into useful knowledge.

References

Ristevski, B., Chen, Ming. (2018). Big Data Analytics in Medicine and Healthcare. Pp. 1-12. https://doi.org/10.1515/may.201810

Discussion 2:

This era has been interlinked with information technology; Internet of things etc. large amounts of  data has been generated in every walk of life. The need of data collection, storing, preparing, processing and interpretation for every industry has become mandatory. Especially Health care systems, retail industry, biometrics, gaming etc. which helps in appropriate decision making, resources allocation details, production related enhancements and consumer reaction towards services etc., were verified and acted accordingly by the management. As mentioned, Big data refers to high volumes of data that is  continuously generated, the challenge raised is extracting it in a right way and used further. I choose data analysis and later this discussion highlights the benefits, challenges related to e-health care industry.

            Data analysis refers to extracting of useful information from immense amounts of collected data by cleaning, transforming and processing it. Considering e-health care industries (Ayani et. al, 2019), data collection exists even before this big data era which mainly consists of data related to diseases diagnosis, number of people effected, status, contagious diseases etc., but challenge is how to understand and present it with greater ease. Analytical tools comes in for survival, they helps to create patterns and establish data set relations which encourages for better treatments, health decisions making, clinical support system. Moreover, US national cancer centers and National institute of health conducted SEER program, provides information related to cancer patients suffering from blood cancer, thyroid, skin and others. To confirm, for each cancer type 300,000 records of datasets were analyzed (leung et.al, 2019).

            Overall, big data has brought some really good revolutionary changes in the industries that made several functionalities and implementation made easy. These analyzed datasets provide convenient data that makes decision making easy.

References

AYANI, S., MOULAEI, K., DARWISH KHANEHSARI, S., JAHANBAKHSH, M., & SADEGHI, F. (2019). A Systematic Review of Big Data Potential to Make Synergies between Sciences for Achieving Sustainable Health: Challenges and Solutions. Applied Medical Informatics, 41(2), 53–64.

Leung, C. K., Zhang, Y., Hoi, C. S. H., Souza, J., & Wodi, B. H. (2019). Big Data Analysis and Services: Visualization on Smart Data to Support Healthcare Analytics. 2019 International Conference on Internet of Things (IThings) and IEEE Smart Data (SmartData), 2019 International Conference On, 1261–1268. https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00212