Introduction
The types of financial data that are used by the Sony Corporation include statements of assets, liabilities, cash flow, expenses as well as income. Assets are the properties acquired by Sony strictly for business use. Contrary, the liabilities are the financial legal liabilities that are incurred by Sony in the course of executing its trading operations. Also, cash flow data is the difference in the available cash in Sony at the beginning of the accounting period and the cash at the end of the corporation's financial period (Lee, 2014). Expenses are any money that is incurred by Sony while the company is trying to generate revenue. The non-financial data that is utilized by Sony include the company's social, environmental and human rights information. Other data include the company's social as well as governance information (ESG). Both financial and non-financial data are utilized by Sony during the organization's decision-making process. Sony also has a good infrastructure of safeguarding its data integrity. The strategies used by the company include offering data entry training to all its personnel and enforcing accountability among the staff for any problems that may be caused due to problems in data entry. Strict disciplinary actions are taken on all personnel who compromise the quality of Sony's data.
Furthermore, Sony has quality data validation rules that are utilized in promoting data integrity in the organization. The primary rule is that all data must be verified twice prior to official submission. Lastly, Sony implements data cleaning periodically in all its financial periods. Through data cleaning, all corrupt and inaccurate information is removed from the corporation's information database (Haldorai, Anandakumar, Ramu, & Arulmurugan, 2018). Nevertheless, there exists a gap in identifying the right documents to preserve and which documents to discard during the data cleansing process. Sony Corporation uses semi-automated organization's data mapping technique to coordinate between business functions and data sources in from its respective stakeholders. In this case, the corporation uses the schema mapping technique and it is a process that entails identifying various data objects, which are semantically related and later building information mappings between them (Wang, 2014). After the schema mapping has been used, a programming code created using Java, C++ or C# is generated and it is employed to fulfill the desired data conversion tasks. In addition, the schema mapping technique is advantageous to the Sony Corporation because it minimizes the time taken in adding new sources of information on the company's database. Moreover, the method allows a small group of information team to manage a large data set.
Data Flow Between the Organization and Its Stakeholders
There are six primary stakeholders at the Sony Corporation. They include shareholders, customers, employees, suppliers, business partners and local communities. The stated stakeholders affect the three decision making ranks in the organization. The ranks include strategic, technical as well as operational decision making ranks. The data flow methods to be used by the company include the upward, downward, external and horizontal/diagonal methods. Upward flow is whereby data moves from the low to high rank stakeholders, while downward flow is the vice versa (Guffey & Loewy, 2010). Contrary, horizontal or diagonal data flow is where information moves between departments or personnel in the same level at the organization. Lastly, the external flow is the movement of information from an audience that is outside an organization.
Implementation of a Big Data Analytics Framework
An analytical framework is a model that explains how a certain form of analysis is performed (Sajjad 2014). In reference to the Sony Corporation, it is essential to develop a good data analytical framework, which can be utilized to assess the quality of data obtained from different sources and utilized for operational purposes. Financial data, for instance, is sensitive and its misrepresentation could affect the overall performance of an organization. As such, it is essential to develop an effective strategy that can be utilized to define the parameters of data quality in an organization. Among the most effective methods that Sony Corporation can utilize to develop a complex analytical framework for assessing the organization's data quality is the utilization of fundamental and largely utilize concepts of enhancing data integrity in an organization. In this case, for instance, there several approaches that can be utilized in improving data integrity at Sony Corporation to promote the large data analytics framework.
Such approaches include performing regular data cleaning and maintenance, minimizing the sources of data to reduce the margin of errors and executing data entry training to all the corporation's personnel. In addition, the training of employees in reference to upholding data integrity at the Sony Corporation should be made a compulsory undertaking to both onsite and new employees. The repercussions for mishandling data should also be made clear to all the personnel functioning at the Sony Corporation's premises. Moreover, Sony should ensure that there is a heightened level of accountability among all its personnel who handle data in the organization. Other approaches should be inclusive of creating standard data definitions, automations in data entry and also ensuring that there is data validation in the organization. Validation will be effective in reducing instances of errors that could be caused by manual data entry (Morgan, 2006).
Data Protection and Ethical Insurance Requirements
Data protection in an organization is the process through which an entity goes through in protecting all forms of data from corruption, loss as well as compromise. In a company like Sony Corporation, the importance of protecting data in the institution increases as the scale of data developed as well as stored in an institution continue to increase. Today, most companies have essential data protection policies, which ensure that organizations remain competitive in the market. Sony Corporation has several data protection requirements. Transparency is the first data protection requirement and it mandates that all data must be processed fairly, lawfully as well as in a transparent manner (Marr, 2015). Additionally, data minimization requirement mandates that all forms of inaccurate data in an organization should be erased or rectified without any forms of delay. The other requirement is integrity and confidentiality. The requirement requires that all forms of data to be protected through the use of the right security measures. Contrary, the ethical insurance requirements by Sony in reference to data protection includes the use of trust, security as well as privacy from all personnel handling sensitive operational data in the organization.
References
Guffey, M. E., & Loewy, D. 2010, Business Communication: Process and Product, Boston: Cengage Learning.
Haldorai, Anandakumar, Ramu, & Arulmurugan 2018, Cognitive Social Mining Applications in Data Analytics and Forensics, Hershey: IGI Global.
Lee, T. A., 2014, Cash Flow Reporting (RLE Accounting): A Recent History of an Accounting Practice, New York: Routledge.
Marr, B., 2015, Big Data For Small Business For Dummies, New York: John Wiley & Sons.
Morgan, J., 2006, 'As' Applied ICT (Edexcel), London: Payne Gallway.
Sajjad, F. (2014). An Analytical Framework for Workflow Technology Adoption in Local Government Authorities. London: Brunel University.
Wang, H., 2014, Innovative Techniques and Applications of Entity Resolution, Hershey: IGI Global.
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