Data Collection And Analysis For Cloud Computing Technology In Medical History Storing

Data Collection Process

Medical history storing and the sharing of files to the public clinic that also by the process of cloud computing technology is the developing process to maintain the information in the medical field. This process is effectively developing in the numerous field of working function with the rapid development of technology in the world. The primary purpose of the report is to provide an effective assessment of the data collection procedure and the analysis for achieving the effective result on the research topic.

1. Data collection

Data collection or gathering is the method which helps to assemble evidence from the various sources to understand the process and the development of research within the field. The collection of data is being performed by secondary as well as the primary sources to gather the information regarding the medical history storing as well as sharing among the public clinic by the help of the could computing technology (Palinkas, Horwitz, Green, Wisdom, Duan, & Hoagwood, 2015). The information is being selected and analysed by the help of test hypotheses as well as the evaluated outcomes regarding the research paper for the development of research topic within the field.

The data source is the connection set-up of the database from the servers. It is the source that effectively provides the view on the various sources of data that has been utilised analysis of the research paper. The various data source that has been utilised within the paper is the public place that is malls and the public stations, then the college or the universities and also various companies regarding the assortment of the documents.

The collection of data is being the process which helps to enhance the research paper and the development process within the field. The primary data is being collected from different public sources and the entire process if free of cost to perform in the field (Cleary, Horsfall, & Hayter, 2014). Below table provides the view on the procedure of data collection as well as effective need of information for the research topic to understand regarding the development of cloud computing technology in the medical history of storing.

Table 1: Data Collection

Name of Data source	Source organisation	Description of Information	Information file format	Duty Fee	Target Information Source
Data 1	Public	Is cloud computing technology suitable for the organisation?	txt	Free	Yes
Data 2	Public	Ways utilised by medical to store their history?	txt	Free	Yes
Data 3	Public	Is the cloud computing technology suitable for sharing data among the public clinic?	txt	Free	Yes
Data 4	Public	What is the pros and cons of using cloud computing technology within the organisation?	txt	Free	Yes
Data 5	Public	What is the security level for sharing information of the medical history to the public clinic with the help of cloud computing technology?	txt	Free	Yes

Data storage within the research paper is the general term that is being used for achieving data in the various form like the public information for the use of analysis by the device. Data storage allow the researcher to maintain their collected raw information for the analysis. This is one of the most effective processes to maintain the information and keep the confidentiality of the raw data that has been collected from the various public sources. The number of data collected for the research paper helps the researcher to select the best and the suitable information for the analysis of the research topic.

Data Storage

Table 2: Information storage

Information source name	Date of gathering	location of Saved files	Name of Saved files	Format of Saved files	No. of information records
The examination from the communal places	09/08/2018	//rare data/	Cloud computing Assessment.txt	txt	70
Investigation from college	12/08/2018	//rare data/	Cloud computing Assessment.txt	txt	80
Investigation from companies	15/08/2018	//rare data/	Cloud computing Assessment.txt	txt	40

Design as well as implementation are one of the essential parts in the term of data selection for the analysis. The design and implementation show that not all the information gathered from the survey is necessary and this phase help to adjust the suitable and the effective information for the analysis of the research topic. This is one of the vital steps for the researcher to maintain their raw data collected from the public sources to analyse the information and provide a suitable outcome on the research topic.

Data preprocessing is the technique of data mining which includes the transformation of the raw information in the understandable layout. It can be seen that the real world data that is being gathered from the numerous respondents in the field survey are mostly incomplete. By the help of the data pre-processing the research is able to solve this issue and provide the best result by depending on the collected information from the survey (Ramírez-Gallego, Krawczyk, García, Wo?niak, & Herrera, 2017). In this research paper, numerous information has been collected from the colleges and the public places and also from the companies on cloud computing technology and the storing of medical history where most of the information was incomplete. To maintain the information and the data that has been gathered within the field allow the researcher to understand the effective process for the analysis of the data.

The dimension reduction is the procedure by that the researcher is eligible on behalf of reducing the number of random variables under the consideration by the process of obtaining the set of the principle variables (Nassirtoussi, Aghabozorgi, Wah, & Ngo, 2015). This process eventually helps the researcher to get the most appropriate data or the information that is being suitable for the development and the analysis of the research paper. The data or the information are being selected by the various process of the pre-processing method to gain the most suitable and effective information regarding the medical history storing and sharing with public clinic via cloud computing technology.

Table 3: Assortment or lessening of data

Date	Name of data source	Purpose of Preprocessing	Method of Preprocessing	Data  record (unique)	Data record (end result)	The new data file name
18/08/2018	Data 1	Spotless the mining information	Documents filtering	190	167	Final-assessment.txt
18/08/2018	Data 2	Avoid unfaithfulness	Documents cleaning (reduction)	150	110	Final-assessment.txt
18/08/2018	Data 3	Feature assortment	Evidence integration	100	80	Final-assessment.txt
18/08/2018	Data 4	Data filter	Information reduction	90	75	Final-assessment.txt
18/08/2018	Data 5	Feature selection	Information reduction	80	70	Final-assessment.txt

The experience scheme is being performed by the help of effective knowledge and skill regarding the process. The methodology selected in this process is one of the best ways to provide the valuable outcome for the research topic. It can be seen that the experiment design allow the researcher to develop their view and their understanding regarding the process and also allow them for the improvement of various skill and knowledge in term of the research topic. Both the qualitative and the quantitative method allow the research to maintain their view and their data collection process in the most suitable and effective way (Eyring et al., 2016). The below table provides the valuable view on the expected outcome of the research paper from the analysis of the raw data that has been collected for the various public places.

Data Preprocessing

Table 4: Experiment designing

Date	Experiment	Persistence of the experiment	Explanation of process	Contribution data	Predictable output	Result file name
20/08/2018	Experiment 1	Evaluate methodology	Gather the information from the public places	Provide questionnaires	Suitable answer and response to the various questionnaires	Output1.txt
20/08/2018	Experiment 2	Evaluate methodology	Prepare for the personal interview	Provide close-ended question to the respondents	The appropriate response to the research paper	Output1.txt
20/08/2018	Experiment 3	Evaluate methodology	Maintain and storage of the raw data	Perform data mining and data integration process	Achieve the most effective and suitable information for the research topic	Output1.txt

The implementation of the experiment within the research paper allows the researcher to maintain their information and their development process within the field (Marzband, Yousefnejad, Sumper, & Domínguez-García, 2016). The experiment, as well as the result, is being implemented within the research paper by the help of the percentage analysis and the response data.

Table 5: Survey question and the response of the participants (total participants = 190)

Questions	Response (number and percentage)
Is cloud computing technology suitable for the organisation?	167 (87%)
Ways utilised by medical to store their history?	110 (57%)
Is the cloud computing technology suitable for sharing data among the public clinic?	80 (42%)
What is the pros and cons of using cloud computing technology within the organisation?	75 (39%)
What is the security level for sharing information of the medical history to the public clinic with the help of cloud computing technology?	70 (36%)

Graph 1: Answer to the survey questions in the research

The graph shows the response of the public in numbers that are being utilised for the research paper to understand the facts and the figure regarding the research topic. The graph represents the various number of response that is being provided for each of the survey questions. 

Graph 2: The percentage of response to the survey question

The expected result for the research paper is that people are very much aware of the cloud computing system and with the development of time they are using this process effectively within the medical system. This is the primary expectation of the research outcome to have the clear view on the use of cloud computing technology within the market and also its drawback regarding the process within the field. The experiment is done to achieve the effective result on the process and provide a valuable outcome for the development of cloud computing technology.

The very first result that could be achieved form the survey is the idea or the concept regarding the fact that whether the cloud computing technology is suitable for the organisation or not. This is the primary and the most effective response in the research paper as this help to understand the need of could computing technology within the modern business world. 

1. Outline of experience and Result analysis

The outline of the experience and the analysis are provided below;

• Data gathering or collection
• Data or information sources
• Gathering of data
• Storing of information or information 

• Design as well as application of the experiment
• Information preprocessing
• Information reduction or feature selection
• Experiment design
• Implementation 

• Result Analysis
• Consequence estimation
• Outcome summary

Conclusion 

The paper eventually concludes the facts that the data is being collected by the help of effective view and the working function within the field regarding the cloud computing technology within the process of sharing files and medical history to the public clinic. The paper also provides the effective view on the collection of data or the information from the field survey to analyse the information and to gather effective communication process within the field. 

References 

Cleary, M., Horsfall, J., & Hayter, M. (2014). Data collection and sampling in qualitative research: does size matter?. Journal of advanced nursing, 70(3), 473-475.

Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937-1958.

Marzband, M., Yousefnejad, E., Sumper, A., & Domínguez-García, J. L. (2016). Real-time experimental implementation of optimum energy management system in standalone microgrid by using multi-layer ant colony optimization. International Journal of Electrical Power & Energy Systems, 75, 265-274.

Nassirtoussi, A. K., Aghabozorgi, S., Wah, T. Y., & Ngo, D. C. L. (2015). Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment. Expert Systems with Applications, 42(1), 306-324.

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544.

Ramírez-Gallego, S., Krawczyk, B., García, S., Wo?niak, M., & Herrera, F. (2017). A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing, 239, 39-57.