Data is an essential asset in an organization. Data incorporates all the other crucial assets in an organization included human resources, facilities, the organization's brand, and capital. Therefore, technological advancement in an organization involves the introduction and implementation of the data governance concept, which is an essential part of the organization. The application of data governance concepts in any organization requires step by step implementation. Thus, a company starts small data governance management, which translates to an extensive system and spread within and outside the organization. Ultimately, the company integrates employees, its processes and operations, and technology to reap maximum benefit from data governance.
There are three primary aims and objectives of data governance. First, data management ensures there is data quality in the organization. Data quality is assessed through its ability to capture all the necessary aspects of the organization and the clients. High-quality data has to be completed to enhance its validity. Organizations rely on available data to make significant decisions affecting the organization. For example, health care data needs to be complete and valid for it to serve the patients' needs (Ladley, 2019).
The second aim of data governance is to instill an organizational culture where the staff is trained on data literacy. Implementation of data governance requires extensive training on the team to build data governance literary. Therefore, the health organization strives to be a data-driven organization that helps in improving service delivery. With quality data and data literacy, an organization achieves the third aim of data organization, which is the maximization of the utilization of the available data. The maximization of data used in the organization leads to a considerable reduction in the cost of operation. There is an improvement in quality due to the maximum utilization of the data-driven agendas. As a result, there will be a reduction in the population risk, coupled with enhanced data handling experience in the organization.
An organization achieves positive results from data governance implementation when there is an active division of roles in data governance. These roles are subdivided into three primary categories, which include; senior leadership, data governance committee, and data stewards. The senior leadership in data governance serves as the driving force in data governance. They ensure that the staff is empowered to handle data governance. They provide an opportunity for the team to train as well as addressing the possible bottleneck of events in the data governance strategies. The data governance committee has the responsibility of coordinating activities in the organization. They provide useful information regarding the data literacy, quality, and utilization in the organization. In a health care system, they are equivalent to the (Electronic Health Records) HER (Ladley, 2019).
Data steward refers to the role played by those who are in direct contact with the implementation of data governance. Thus, data steward is a tool for information and optimization of the data governance strategies and techniques. A data steward is critically essential because it helps in reinforcing principles, practices, and directions that are in support of the data governance concept. They feed the data governance committee with important information that helps in the implementation of the idea and strategies of data governance.
There are three primary cultures in the data governance concept. These cultures include tribal governance, where data governance is left to take its course. In this governance culture, all the stakeholders are left to think for themselves and make relevance data governance decisions. The data governance committee does not come together to solve the problem and achieve a common goal. Therefore, this culture results in poor decision making because people involved in the decision-making process are not sure or lack sufficient knowledge about the concept of data governance. There is a departmental conflict in an attempt to solve the problems and make a decision.
Authoritarian modal is another way of looking at data governance culture. The authoritarian modal involves restriction of access to the data. Therefore, the decision-making process is slow and requires a wide range of operations. There is no connection between the upstream and downstream sides of data governance. For example, the decision-making process would involve making a request and wait for the application to be processed. There is no means of determining what is taking place in the process because of the restricted access.
Democratic data governance is the other culture in data governance. The democratic concept in data governance involves a set of rules, established committees, and a transparent data request mechanism. The most striking aspect of the culture is the delegation of authority in data governance. In the democratic data governance culture, the data governance committee is the equivalent of the Supreme Court in the legal system. They are responsible for the delegation and mitigating issues relating to priorities in data governance.
The health organization employs data governance techniques that capture the details of the patients and the staff. The implementation of data governance in the health care system has enabled the health providers to overcome the system barriers. Data governance has provided expert analysis of the EHR system in the organization. It has created a possibility for automatic report generation in the organization reducing the time of operation. The data democracy in the health organization has been an essential tool for creating awareness of the health practices and influencing the patients to take action. However, the implementation of the data government concept experiences stiff challenges emanating from the security concerns of the patients. The patients need a system that will assure them that the data they offer to their health providers will be safe. Therefore, there is a need to implement security systems that will ensure that the staff can access and use the data governance technique when they are in their working premises only. Data access restriction will ensure that no worker can manipulate of misuse the patient's information.
Ladley, J. (2019). Data governance: How to design, deploy, and sustain an effective data governance program. Academic Press.
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Essay Sample on Data Governance: Step-by-Step Implementation for a Successful Organization. (2023, Mar 16). Retrieved from https://proessays.net/essays/essay-sample-on-data-governance-step-by-step-implementation-for-a-successful-organization
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