What is data governance? In its most simple form, data governance is the management of information that is crucial to the workings of a company. It is important for there to be an interest in the data that exists and the users must be able to have access to it and to make sense of it. There are three major forms of data governance at work today;
The first form is called data privacy. This is largely political in nature and refers to the rules that govern who can make use of the data sets as well as who can look at them. For example, one might consider the collection of data on a database at the White House and the rules that surround that data privacy. There may be rules about how emails can be deleted as well as rules about what kinds of documents need to be handled and who needs to look at those documents before they are deleted.
Data governance in this context refers to the systems and procedures that are put into place to maintain the integrity and confidentiality of that information. The information is managed according to agreed-upon rules and guidelines and the access to data sources is controlled. It is often part of an organization’s data cataloging system. The cataloging system is the set of processes that identify which data sources are available to a given organization and which ones are not. It also manages the storage of that data and access to it.
Data governance can also refer to processes involved in the identification, selection and use of security processes such as encryption, access control and identification. It can also refer to the review of those processes and their results and the management of the risks that are associated with those selections. These processes are part of the responsibility of a data security manager and include determining how the data can be protected, what risks there may be and how best to protect them, monitoring and controlling access to data, implementing policies for controlling access and balance checking procedures.
Data governance also includes the periodic review of compliance parameters associated with the activities of the data management process. One example is when changes are being made to the security rules of an organization. Changes can require updating of the governance process. governance is important not only for end-users, but also for the organization as a whole. It is the way in which the end-users of a business will be able to access, manage and utilize the data in the manner that they need and at the manner that is most convenient for them.
The primary goal of data governance processes is to provide businesses with the protection and integrity necessary for the data used by the business. There are two main objectives of governance: protecting the data used by the business and ensuring that the business delivers the services that it promises. There are four main data governance processes: users, operational, process and regulatory. Users may include decision-makers, managers, staff and other employees of the business organization; Process may include information flows, human resources, sales, supply chain, production, engineering etc… while Regulatory may refer to authorities responsible for ensuring that these processes go smoothly and meet the requirements of the legal framework.
Data governance ensures that business units are able to have a clear picture of the purpose and users of the data. This also ensures that the business units are able to make informed decisions about the use of the data and about the security of the data. For instance, when users access data from one business unit, they know what the user is after and how the user wants to get the information. This gives business units a competitive advantage because they are better able to offer and sell the services that the users are looking for.
There are also some governance initiatives that aim to build user loyalty, build partnership, maintain good relationships with customers and suppliers and build productivity. It also aims at increasing data quality. One such initiative is master data management. The objective of master data management is to provide consistent and accurate information in all areas of a business organization. By building trust and partnership with customers and stakeholders, business units become more resilient and better positioned to derive the maximum advantage from their data.