Main Menu

My Account
Online Free Samples
   Free sample   Business analytics and modelling assignment on the impact of data analytics on different industries

Business Analytics and Modelling Assignmenton the Impact of Data Analytics on Different Industries


Task: Write a reflective journal on computer architecture assignment analysing the theoretical concepts captured from the weekly material.


1. Executive summary
This Business Analytics and Modelling Assignment will explore the role of data modelling in the healthcare sector. The global economy is an ever changing and competitive landscape, which demands innovation, advancements and developments in technology. The big data analytics is one such development which has impacted different industries and changed the world of business. The Business Analytics and Modelling Assignmenthighlights the importance of the healthcare sector. The study shows how the industry used to operate traditionally before the introduction of big data analytics in healthcare. The big data analytics in healthcare has helped in expediting various operations, improving the efficiency of the services and enhancing the effectiveness of the industry as a whole.

2. Industry background
As per Business Analytics and Modelling Assignmentresearch the healthcare industry falls under the umbrella term which consists of medical professionals, medical devices, hospitals, clinicaltrials, telemedicine, outsourcing, health insurance, medical tourism, medical equipment, etc. The healthcare has always been a booming industry because the need for healthcare services never ends (Martínez-Caro et al, 2018). The advent of technology and advancements in medical science has led to the brisk growth of the healthcare industry. The governments of various countries are trying to strengthen their healthcare sector as they know health will bring wealth to the nation. The Business Analytics and Modelling Assignmentresearch also shows governments of most of the nations across the world is aiming at increasing the healthcare coverage, improving the quality of healthcare service and raising the public expenditure on healthcare (Siskoet al, 2019). The nations are trying to increase the scope for private investment and growth in healthcare industry. A strong and good healthcare industry is important for any country. A sound healthcare system facilitates reducing the burden on the citizens and makes a significant contribution towards the national growth. The economy is strengthened through an efficient healthcare system. As per Abaaset al(2018), a rise in the life expectancy at birth by 10 percent would ensure a 0.4 percent economic growth every year. However, this crucial sector was running differently until it adopted data analytics. The healthcare industry followed the traditional care delivery model. The healthcare sector comprises of various segments like healthcare facilities and segments, medical equipment, devices and hospital supplies’ manufacturers, medical services, medical insurance and managed care, pharmaceuticals, etc. These segments are interrelated and were earlier connected in their operations without the use of data analytics. The lack of analytical support led to delay in operations and errors. The data analytics has enhanced the quality of services of healthcare industry, making the sector more effective and efficient. However, the physicians feel that their role has been minimised by data analytics. The data analytics has disrupted the personal association between patients and doctors. The data of the healthcare industry is very crucial because it is related to the life of humans. Thus, a proper Business Analytics and Modelling Assignmentanalysis of the data could open new gateways and exploit better opportunities for improving the quality of life and care for people (Mehta and Pandit, 2018). Prior to the implementation of big data analytics in healthcare, the industry used to operate traditionally. This implies that the data was stored manually into systems without automation, the clinical treatment did not have the analytical support, the diagnosis was delayed, the maintenance of case histories was a challenge, and much more (Khanraet al, 2020). The adoption of big data analytics in healthcare is a blessing for the medical professionals as well as the patients and their families.

3. The impact of Business Analytics and Modelling Assignmentdata analytics
The evolution of technology and the introduction of big data analytics has changed the face of healthcare industry. The big data analytics as suggested by Kumar and Singh(2018), has provided a better and deeper insight into the process of clinical treatment. This facilitates informed and better decision making by the medical professionals about the diagnosis and the treatment to be provided to the patients. The big data analytics enables prevention of the diseases. Furthermore, through the use of big data analytics the efficiency of the operations of the healthcare industry has been improved. The data potential is realised through the implementation of big data analytics (Galetsi, Katsaliaki and Kumar, 2019). There are several benefits of using big data analytics in the healthcare industry. There are certain areas in healthcare which have been facilitated through big data analytics. These include the support which big data analytics has provided to the clinical treatment which ensures better treatment decisions by the medical professionals like physicians, dieticians, nurses, etc. The accuracy of the healthcare services have been enhanced through big data analytics. The speed of execution of various operations of healthcare has been increased with the help of data analytics. The advantage of big data analytics is that the diseases are diagnosed easily and the treatment is initiated sooner. The electronic health records (EHRs) include more details about the patients which fosters better healthcare services (Sousa et al, 2019). Data analytics is used in healthcare for analysing the large database of the patients, for making payment transactions easier, for diagnosing diseases, etc. AI based NLP system is used for classifying and understanding clinical documentation. As per the Business Analytics and Modelling Assignmentfindings Machine learning facilitates the analysis of external data for X-rays, CT scans, screenings, etc. improving the quality of treatment.

4. Conclusion
It can be concluded that big data analytics has changed the entire scenario of the healthcare industry. The big data analytics has shaped the present and is setting the future of the healthcare industry. The opportunities of big data analytics lie in its advanced information management, effective responsiveness, increased visibility of supply chain, efficient maintenance and operations, transparency, etc. which will enhance the performance of the healthcare industry. The challenges of big data analytics are that it fails to offer timely and proper insights, involves complicated operations, makes inaccurate analysis, takes long time to respond, requires adequate funds for maintenance, etc. The lack of funding and skill to handle big data could pose a challenge to its adoption in healthcare. There are certain ethics involved in big data analytics as it deals with human data and information. These include the ownership of individuals over their data, transparency of transaction in personal data, allowing easy access to the algorithm design, etc. The risk of big data analytics is mainly pertaining to the security and privacy of the data of the owners. It has been established on the Business Analytics and Modelling Assignmentthat a company’s big data should not go in wrong hands, otherwise it could lead to problems like scams, phishing, spreading of disinformation, etc.

Abaas, M.S.M., Chygryn, O., Kubatko, O. and Pimonenko, T., 2018. Social and economic drivers of national economic development: The case of OPEC countries. Problems and Perspectives in Management, Business Analytics and Modelling Assignment(16, Iss. 4), pp.155-168.

Galetsi, P., Katsaliaki, K. and Kumar, S., 2019. Values, challenges and future directions of big data analytics in healthcare: A systematic review. Social science & medicine, 241, p.112533.
Khanra, S., Dhir, A., Islam, A.N. and Mäntymäki, M., 2020. Big data analytics in healthcare: a systematic literature review. Enterprise Information Systems, 14(7), pp.878-912.
Kumar, S. and Singh, M., 2018. Big data analytics for healthcare industry: impact, applications, and tools. Big data mining and analytics, 2(1), pp.48-57.
Martínez-Caro, E., Cegarra-Navarro, J.G., García-Pérez, A. and Fait, M., 2018. Healthcare service evolution towards the Internet of Things: An end-user perspective. Technological Forecasting and Social Change, Business Analytics and Modelling Assignment136, pp.268-276.
Mehta, N. and Pandit, A., 2018. Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, pp.57-65.
Sisko, A.M., Keehan, S.P., Poisal, J.A., Cuckler, G.A., Smith, S.D., Madison, A.J., Rennie, K.E. and Hardesty, J.C., 2019. National health expenditure projections, 2018–27: economic and demographic trends drive spending and enrollment growth. Health affairs, 38(3), pp.491-501.
Sousa, M.J., Pesqueira, A.M., Lemos, C., Sousa, M. and Rocha, Á., 2019. Decision-making based on big data analytics for people management in healthcare organizations. Journal of medical systems, Business Analytics and Modelling Assignment43(9), pp.1-10.


Related Samples

Question Bank

Looking for Your Assignment?

Search Assignment
Plagiarism free Assignment









9/1 Pacific Highway, North Sydney, NSW, 2060
1 Vista Montana, San Jose, CA, 95134