The use of data is a vital and extensive process that is integrated into human beings’ lives in various contexts, from the personal aspect to the business and managerial aspect. The data life cycle has numerous stages, from the data creation stage to the final stage, data destruction or disposal. In between this cycle, one of the most vital stages is the data processing stage which has its strategic process used to make the raw data collected more utilizable for the intended functions. The data processing cycle can be applied to any data set effectively, as demonstrated in the elaborative example explored in this report.
The six stages of data processing include Data Collection, Data Preparation, Data Input, Data Process, Data Output, and Data Storage (iTech, 2021). The real-life case that will be utilized is a case scenario I was required by a company I was interning with to assess our new product’s impact on its sales and how it might affect future operations. In this project, I certainly required data that was crucial to gaining the insights needed since I needed to make analyses and find correlations between the introduction of the new product and the company’s sales growth.
For this project, this was the first step regarding the data used. The step involves using various data collection tools to gather and pull all the relevant information regarding the subject of interest (Periyar Government Arts College, n.d.). Under this step, I utilized the company’s sales records and questionnaires administered to customers through an online survey. These techniques were vital for this step.
The data preparation stage involves cleaning the raw data to make it suitable for data entry (Periyar Government Arts College, n.d.). Notably, this stage is preferably conducted by one individual to enhance accuracy, consistency, and data standardization as these have an inverse correlation with the high number of people performing the data preparation process (Goben & Raszewski, 2015). Under this stage, I used software, Tye, to clean, standardize and validate, correct, remove duplicates and enrich the data collected from step 1.
The data input stage involves entering the data into the system using various approaches. Notably, this is the first step in which data starts taking a more utilizable shape (Periyar Government Arts College, n.d.). In this project, I used machine encoding and manual data entry to enter the data into the company’s system.
The data processing step is the most vital as it involves using electronic, mechanical, or automated techniques to transform the raw data into information that the end-user can utilize. Under this step, I used various techniques such as mathematical and statistical models and automated data analysis softwares to analyze the data.
The data output step is a direct product of the data processing stage, which provides the analyzed data as either information or results (Periyar Government Arts College, n.d.). Further interpretation of the processed data using software or user’s knowledge might be needed to add quality to the insights. I provided more utilizable data in tables, graphs, and other elaborative formats for this stage. I also used my experience and knowledge to interpret the implications of the insights gained on the company’s future operations.
The data storage step is the final step of data processing. The step involves securing the data and storing it in highly reliable systems for future use (Periyar Government Arts College, n.d.). Under this stage, I used the cloud services provided and utilized by the organization to store the data for the company to use in the future. The cloud-based storage option offers highly reliable data storage services despite presenting drawbacks such as susceptibility to data breaches, privacy issues, and maintenance costs (Obrutsky, 2016).
Data as Valuable Currency in Business
Data and the overall processes involved in making the data utilizable is regarded as a valuable currency in business since it offers insights that better business engagements, the services offered, and targeted offerings that increase the businesses’ sales and revenue (Barratt, 2019). Therefore, data is a vital currency in the current business field.
Barratt, J. (2019). Data as Currency: What Value Are You Getting for It?. Knowledge@Wharton. Retrieved 12 February 2022, from https://knowledge.wharton.upenn.edu/article/barrett-data-as-currency/.
Goben, A., & Raszewski, R. (2015). The Data Life Cycle Applied To Our Own Data. Journal of the Medical Library Association: JMLA, 103(1), 40.
iTech. (2021). What is Data Processing: Definition, Cycle and Types. iTech Data Services. Retrieved 12 February 2022, from https://itechdata.ai/types-of-data-processing/.
Obrutsky, S. (2016). Cloud storage: Advantages, disadvantages and enterprise solutions for business. In Conference: EIT New Zealand.
Periyar Government Arts College. Research Methodology. Pacc.in. Retrieved 12 February 2022, from https://www.pacc.in/e-learning-portal/ec/admin/contents/22_MCM34_2020112906462433.pdf.