Describe the business rules and their relationship to effective data management.
Data management is an asset for the companies that includes into the production and manufacturing activities. The value of the data is quite difficult to be valued, as it can be done with the corporate assets of the company. Data of the company has to be effectively handled and used for improving the intelligence environment within the company. The data quality, its role for the business improvement, and other relevance has to be analysed by the management. This will enable the company to face different challenges that exists at the workplace. By implementing an effective data analysis method, it is possible to introduce data management program, which will assist the company (Business Rules Forum, 2008).
Data management system is a process through which the roles, policies, responsibilities, and procedures related to the maintenance, acquisition, disposition of the data, and dissemination is planned and executed. There is a direct relationship between the data management model and dissemination is handled. Through this method, the company develops or partners with different technology groups and ensure to use the data quality management system in the best possible manner. Business rules are established, so as to ensure that the response system can be developed for evaluating the quality of the acquired data (Fard et al., 2010).
Information technology department or team of the company are responsible for handling different tasks like the technical facilities, architecture, databases, systems and others. Such process helps in acquiring and maintaining the electronic data assets possess by the company. Business operational activities include decision making and rendering the best possible services to the customers. Planning for rendering such services are done on the basis of the collected data from different resources. Data warehouse is used for examining the changing business trends. Such an analysis would help in developing and implementing an effective strategy that will be useful for accomplishing the tasks for the future. Every company strive for improving the customer relationship management system. In this factor, data is collected regarding the customer preferences, expectations, and other factors. This will help in making the accurate decision through which the required changes for business execution can be introduced. Financial data can be retrieved to check the profitability possibilities for the company. Good data and appropriate usage of the same is an important strategy (Jun et al., 2006).
Entity relationship model is an ideal option for handling the important data about the company. The data model describes the information or the data important for handling the process requirements. The database is associated with the relational database.
Entity relationship model is defined as a systematic way for describing or defining the process of the business conduct. The components of the business are linked with the dependencies or the requirements that exists between different components (Kamalian et al., 2010).
The model is used for handling the data management system, which includes the program manager, business analyst, and data analyst. Data quality management program includes reactive and proactive components. In the proactive component the business rules associated with the defining the responsibilities of the company, analysing the quality expectations, and analyse the important supporting business practices. The technical environmental factor has to be analysed as this will help in developing an effective strategy for business development (Khan et al., 2010).
Conceptual data model is considered to be a secured system, which enables the business to use differentiate the references that are used for the data entities. This method is known to be the foundation of the data entity method that is being chosen by the comment. The development of the enterprise conceptual framework model is meant to support the document related to the data architect factors (Latt, 2008).
With the help of the reactive component the problem associated with analysing the data is carried out. In the legacy system, the quality of the data is analysed through different strategies. The inadequate information is excluded from the ones that are considered to be important. Business rules are associated with the adoption of the better strategies that will improve the relationship of the company with the existing and potential clients. The relevance or the usage of the information or data collected by the management can be used for various purposes. The data useful for analysing the customer preferences might not be useful for the financial department. Such a process creates huge problem for the execution of the tasks and using the data in the right manner (Mani, 2010).
Organization change is one of the important policies or rules drafted by the company. The values and benefits associated with the change system have to be understood in an effective manner. This would help the managers to handle the business intelligence environmental factors. The issues arising in this case would help the management in overpowering the challenges involved in the process. Problem associated with the data quality issue are analysed through the implementation of the business intelligence projects. The change program plans an essential role in assisting the company to analyse the relevance of the issues and the methods to deal with the same (Matthew et al., 2009).
Business analysts play a key role in identifying the business requirements like the quality, customer services, technical changes, and other factors. It is essential to include the details into the data quality requirement system. The selection of the data model has to be done after analysing the future of the company and the objectives decided to be achieved by the management. Through the data model, it is possible for the management to develop and implement the best data acquisition method. This would help in improving the delivery process. The quality requirements can be checked and the corrective measures can be introduced within the system. For this, the data requirements can be used for defining the quality requirements, designs, and other factors are closely evaluated. This would help in managing the data, and use the same as the corporate asset. The roles are defined, as this will assist in improving the quality of services proposed to be rendered to the clients (Oluseyi, & Ayo, 2009).
The implement on of the data model for improving the business performance is a complex task. Management has to analyse the challenges involved with the process of implementing the data. This will help in overpowering the issues and introducing the best strategies that would help in business development. It is challenging to introduce a formal data quality evaluation method. Some of the factors required for executing the task have been included below –
The challenge is associated with the single business unit. The business unit use the data that is used for including the response task that is required the data in the best possible manner. The data once stored into the computer don’t willingly take the responsibility for the wrong acts performed by one or the group members. The business rules needs to be integrated with the IT system for the data, which is required for executing different tasks at the workplace. It is necessary to introduce an effective management system for the data quality through which the process can be carried out in the right manner. The caring system has to be lined and introduced in the appropriate manner. This will enable the company to make the people responsible which are required for executing the task. Before investing in the installation of the data management system the benefits has to be analysed. Calculating the profit or benefits associated with such a process is quite a challenging task. This is one of the reasons; the management doesn’t choose to invest in the purchase and installation of the system. Such a factor impacts the willingness of the management to introduce the better system through which the data issue can be used in the right manner. The model selection is one of the challenging tasks and the same has to be correlated with the business rules and objectives. This will help in improving the quality of services intended to be provided to the company (Rynes et al., 2004).
Conclusion
The data management system is quite a crucial factor for the company. Selection of the model and method depends upon various factors like the benefits and the usage of the system. In this case, the challenges involved in the process of implementation of the process have to be analysed. This is necessary for deriving the data that can be used for business management. With the help of the data management system, it is possible for the company to choose the better data, and use the same in the right manner.
References
Business Rules Forum 2008. Practitioners’ Panel: The Real World DOs and DON’Ts of Business Rules,”Business Rules Journal, Vol. 10, No. 3 (Mar. 2009), URL: https://www.BRCommunity.com/a2009/b465.html
Fard, H. D., Ghatari, A. R., & Hasiri, A., (2010). Employees Morale in Public Sector: Is Organizational Trust an Important Factor? European Journal of Scientific research, 46 (3), 378-390.
Jun, M., Cai, S., & Shin, H. (2006). TQM practice in maquiladora: antecedents of employee satisfaction and loyalty. Journal of Operations Management, 24, 791-812
Kamalian, A. R., Yaghoubi, N. M., & Moloudi, J., (2010). Survey of Relationship between Organizational Justice and Empowerment (A Case Study). European Journal of Economics, Finance and Administrative Sciences, 24, 165-171.
Khan, K. U., Farooq, S. U., & Ullah, M. I., (2010). The Relationship between Rewards and Employee Motivation in Commercial Banks of Pakistan. Research Journal of International Studies, 14, 37-52
Latt, K. A., (2008). Motivating People on the way towards Organizational Performance. Victoria University (Australia), intern analyst, Covalence SA, Geneva.
Mani, V., (2010). Development of Employee Satisfaction Index Scorecard. European Journal of Social Sciences, 15 (1), 129-139
Matthew, J., Grawhich, & Barber, L. K., (2009). Are you Focusing both Employees and Organizational Outcomes. Organizational Health Initiative at Saint Louis University
Oluseyi, S., & Ayo, H. T., (2009). Influence of Work Motivation, Leadership Effectiveness and time Management on Employees’ Performance in some Selected Industries in Ibadan, Oyo State, Nigeria. European journal of Economics, Finance and Administrative Sciences, 16, 7-17.
Rukhmani, K., Ramesh, M., & Jayakrishnan, J., (2010). Effect of Leadership Styles on Organizational Effectiveness. European Journal of Social Sciences, 15 (3), 365-369.
Rynes, S. L., Gerhart, B., & Minette, K. A., (2004). The Importance of Pay in employee Motivation: Discrepancies between What People say and what they do. Human Resource Management, 43 (4), 381-394.
Tella, A., Ayeni, C. O., & Popoola, S. O., (2007). Work Motivation, Job Satisfaction and Organizational commitment of Library Personel in Academic and Research Libraries in Oyo State, Nigeria. Library Philosophy and Practice, 1-16
Viorel, L., Aurel, M., Virgil, M. C., & Stefania, P. R., Employees Motivation Theories Developed at an International Level. Labor Management, JEL article code: M54: Labor Management, 324-328
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