In this modern world having knowledge about technology is very important. Most of the organizations have their office in various parts of the worlds. Now–a-days, no organization has limited themselves inside the four walls of the organization. Thus, it becomes very difficult for organizations who have not taken the full advantage of technology. It becomes very difficult for any organization to communicate with their other branches that are not located nearby and using the traditional way of communicating is very slow in nature.
Every organization that is located in just one location or in different locations more or less performs operation on the same type of data. This turns to be a big problem for organizations that have many branches that are not close to one another geographically.
Data governance comes to help in this kind of situation. It is a control that sees to it that data entry that is done manually or by any automated process may meet the precise standards. The precise standards like, any business rule, data integrity constraints and data definition. It is used by organizations to have control over methods and processes used by their data custodians and stewards in order to improve the quality of the data (Bonnet, 2010).
The most important and familiar, i.e. this problem is most likely to occur in the absence of data governance is redundancy in data (Jay & Clarke, 2010). This can be further explained as multiple data present for same type of field, example. In this scenario all the data have to be updated manually in every branch of the organization whereas, if data governance is present in the organization just one update will do. To update all the data will be costlier and work will increase. Their might occur inconsistency in the system if this type of scenario persists.
It will be hard to keep track of the data which is recently updated and there will be no match between the branches of an organization.
If this kind of scenario keep on going it might occur that the data present is not same in different branches in the same organization (Jay & Clarke, 2010). Due to this if any information is needed there is a chance that the data might not be reliable in every branch and thus great chances for error to take place would maximize. This condition will lead to errors and thus the quality of the work will decrease eventually.
The information must be updated and genuine in nature or else it is of no use. Using data that is not relevant now would only cause error in the work (Hill, 2010).
It will become difficult to comply with the regulatory requirements as, it will always want all the information regarding money and account information about anyone to be accurate. There should be no duplicate data present or data that are not relevant.
All these problems can be solved by using a good governance technique. Data governance is a set of process that sees to it that the important data are managed properly throughout all the branches of the organization (Sabel & Zeitlin, 2010). Using this will ensure that time will be saved a lot. It will prove to be a boon for the organization as lesser number of errors will be present. It will help the organization to reduce its financial trouble.
This report clearly suggests the disadvantages and problems relating to this situation. It will be very difficult for the employees to do their work properly and also the organization will suffer financially as well as time consumed to any work done will be more than usual. Thus it can be inferred that having a good data governance system is must for any organization that have many branches as well as those who are confined in one place.
Bonnet, P. (2010). Enterprise data governance. London: ISTE.
Hill, D. (2010). Data protection. Boca Raton, FL: Taylor & Francis.
Jay, R., & Clarke, J. (2010). Data Protection Compliance in the UK. Ely: IT Governance Pub.
Sabel, C., & Zeitlin, J. (2010). Experimentalist governance in the European Union. Oxford: Oxford University Press.
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