Data management is executing and developing the policies, procedures and practices which help in managing the data lifecycle that is mainly needed for the enterprise in a successful manner. This is the administrative part of the system where the data’s are stored, acquired, protected, processed and validated through which the timeliness, accessibility and reliability are ensured in satisfying the wants of information users. Data are the one of important assets of the company (Clougherty and Moliterno, 2010).
In Data management, there are various steps for managing the data. At first the plan is made that how to manage the data and other requirements, then comes the storing of the data where the organization of files is done. The data are secured and back up is made so that if any tampering is done with those data then a back up file is available. Formats are made on files so that it benefits in the long run(Baldoni, 2006).After the storing is done then comes the sharing of the data where the data storing is found and with that requirements of the journals are met. The database management system is an important feature in the sector of IT management where the resources are the idea of “new economy”. The significance of database management is not at all like the filing of information in traditional system but it gives more importance to the current technologies in this field (Wiggins, 2012). Under the data management system there are different sections like- data integration, data preparation for Hadoop, data quality and data governance (Loshin, 2009).
For research work data management is one of the important areas and it is one of the complex tasks in any field. While doing a new project the researchers at first tackle the issues which they might face while doing the work because it’s save their effort and time in the later stage. Data management plays an important role in an organization (Vakali and Jain, 2011). It generates the costs and revenues and lessens the risks. It successfully shares, protects and stores the data and brings a competitive benefit in today’s business. Managing the data results of the customers binds a good relationship with the customers. While expanding, the storage of the data requirements has also increased with investment of the equipments. There are many costs which are hidden are mainly associated with the data management. These costs includes the consumption of current, cooling of this requirements, cabling, backup of this data and recovering them are also done (Liao and Triantaphyllou, 2007).
Detect and interpret the data when it is needed.
Evade undesired duplication.
If required try to prove the results.
Ensure that the research work has its own impact.
Take credits when others commend the work.
Data management plays an important role in the risk area of the organization. Like- establishing a confinement policy which helps in reducing the costs of the storage and decreases the risk assessment (Choi and Huang, 2014).
If there is a loss of data then it is a huge risk for the organization and this matter is generally neglected by the organization and this error causes huge loss for the organization. Loss of data is a risk which causes both in external and internal area of the organization. Loss of data can take place by hacking and also by the negligence of the employee (Bilitewski, Darbra and BarceloÌ, 2013).
Every company both private and public has a review system which processes the data regularly. The information is made up-to dated and the protection and recovery of the data are also important. The infrastructure of the IT sectors is becoming complex. Accurate security policies are made so that the loss of data can be safeguarded. At every step the data are checked daily to confirm that the data are fitting the purposes or not. So, it is important to keep the back up of the data and storing them rightly and if by chance there is a loss of data then there should be way of recovering those data.
In today’s world of technology data management is one of the important factors. Every organization has lot of data which are used every day of for working and managing and securing those data is a very important job. If by any chance any data gets hacked, misplaced or it gets lost then it will create a lot of problems for the organization. So to keep those data secure the organization should keep more than backups so that it does not affects the work of the organization (Richardson and Hoffman-Kim, 2010).
Baldoni, R. (2006). Global data management. Amsterdam: IOS Press.
Bilitewski, B., Darbra, R. and BarceloÌ, D. (2013). Global risk-based management of chemical additives II. Berlin: Springer.
Choi, S. and Huang, X. (2014). Maximum likelihood estimation of semiparametric mixture component models for competing risks data. Biom, 70(3), pp.588-598.
Clougherty, J. and Moliterno, T. (2010). Empirically eliciting complementarities in capabilities: integrating quasi-experimental and panel data methodologies. Strategic Organization, 8(2), pp.107-131.
Liao, T. and Triantaphyllou, E. (2007). Recent advances in data mining of enterprise data. Singapore: World Scientific.
Loshin, D. (2009). Master data management. Amsterdam: Elsevier/Morgan Kaufmann.
Richardson, J. and Hoffman-Kim, D. (2010). The Importance of Defining ‘Data’ in Data Management Policies. Sci Eng Ethics, 16(4), pp.749-751.
Vakali, A. and Jain, L. (2011). New directions in web data management 1. Berlin: Springer.
Wiggins, B. (2012). Effective document and data management. Farnha
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