This paper studies the concepts of information and data governance. It reviews the drivers of these processes and underlines the similarities and differences between them. The paper also discusses how these drivers contribute to the purpose and functions of data and information governance, how they differ and how they can complement each other. It concludes by presenting the examples of possible synergies between the concepts.
The Drivers of Information and Data Governance
Diamond (2014) states that the drivers of information governance are optimized discovery, productivity and collaboration, legal issues and compliance, privacy and security, and defensible disposition. For example, there are many rules that require companies to take records and collect information. Optimized discovery considers the ways to reduce risks and costs for innovation in these processes.
The privacy and security factor underlines that companies have sensitive information and it is necessary to manage it appropriately, ensuring that it is identified and protected. Notably, this aspect corresponds with the drivers of data governance significantly, which will be discussed below. Productivity and collaboration drivers affect the way organizations improve their employees’ productivity in managing and sharing information. If this strategy is poorly implemented, each worker has an individual piece of data instead of a shared database, which can be challenging for the company. Finally, defensive disposition regards the methods an organization utilizes to dispose of expired and low business value records.
The primary driver of data governance is the maximization of the income generation potential of information. It regards the issues of enhancing interaction with customers, and the methods organizations can use to make better business decisions based on analysis of the facts. Other drivers of data governance are increasing consistency and confidence in the corporate decision-making process, improving security and quality of documentation, optimizing personnel’s effectiveness, and establishing process performance baselines to enable improvement.
Purposes and Functions of Information and Data Governance
The difference between the drivers frames a variety of goals and functions of information governance and data governance. The primary purposes of data governance are to ensure that documents are secured and provide the company with the information about the location of its records and the means of access to it. It also aims to present the facts about transmission and utilization of documentation.
It is necessary to point out that, typically, data governance refers to the management of digital information but is not limited to it. For managers, projects associated with data governance may include administration of master data, metadata, enterprise and customer resources.
Information governance, on the other hand, serves to ensure the effective use of information. For example, for managers, information governance policies may include deciding how and for what purpose customers and employees may use certain types of information. In this case, the function of information governance is different from data governance purposes, as it is not necessarily aimed to maximize the income generation potential of the data.
The differences between the drivers of information and data governance promote the differences in the operations that are typical for these processes. For example, information governance may involve record retention, sensitive data classification and placement, and legacy document management. The method of data governance focuses on monitoring and metrics, business intelligence and rules, and data modeling. The differences in the processes show that even though both concepts consider information as their operation source, they utilize it for different purposes.
Differences Between Information and Data Governance
Information governance is different from data governance, although the terms are often used interchangeably. Information governance generally refers to the management of information at a company. Diamond (2014) notes that data governance is a framework that primarily focuses on “big data” to increase the income generation potential of data and enhance the company’s confidence in decision-making. It means that there are some collisions between these practices.
It is necessary to point out that these concepts are not competitive but complementary. For example, information governance considers data privacy, which is complementary to data security representing a part of data governance. Information governance is concentrated on the component of information; it is respectful of privacy regulations, while data security implies the development of an enforcement strategy.
The concept of employees’ productivity and collaboration ensures that the organization shares the right information with its employees, and is usually implemented at the document level; it complements the data governance’s factor of documents and control. Document retention and disposition consider for how long the organization keeps the records, which is connected to the concept of data storage and operations used in data governance. The examples show that good information governance strategies result in effective data governance strategies (Diamond, 2014).
The area of data mapping should be reviewed separately as it is complementary to the metadata and data dictionary. A well-defined data map shows what information is currently available and how it can be accessed. At the same time, metadata, as a part of data governance, defines the core source of data and where it is situated, which means that the concepts correspond with each other. Moreover, many companies try to develop their data mapping strategy through data dictionary projects, which is useful for structured information. Mapping of records is an essential part and the intersection between information and data governance.
Possible Synergies Between Information and Data Governance
Information and data governance serve different purposes but should be coordinated and implemented into the company’s policies. For example, managers can use the principles of information governance to decide what materials can be available to customers as a part of the company’s strategy for sales. At the same time, they can utilize the methods of data governance to enhance interaction with the clients and ensure that the records have the income generating potential.
Moreover, with information governance, managers can ensure that sensitive information is defined and protected, while the principles of data governance can be used for developing the methods of increasing the data security. Finally, data mapping may be utilized to define the available records, while data governance can identify the sources the organization uses to receive the facts.
The concepts of information and data governance are often used interchangeably; however, they serve different purposes. The drivers of information governance include optimizing discovery, productivity, and collaboration with the customers and employees, legal issues and compliance, privacy and security, and defensible disposition; the concept considers the effective use of data. The drivers of data governance include maximization of income, consistency in decision-making, ensuring data security and quality, and optimizing staff’s productivity.
These concepts have different purposes and functions but contribute to one another, since both of them consider data mapping, security, and the effective use of information. Information and data governance can be used in collaboration to achieve better results for the company’s performance.
Diamond, M. (2014). What’s the difference between information governance and data governance? . Web.