The term data governance refers to the process of managing data in an organization. Organizations capture vast amounts of data, sometimes through thousands of interfaces. In addition, data is often captured by more than one business unit, each of which may develop its definition of data and classification. This creates potential conflict when data is handed off and inconsistent application of data handling policies. Data governance is an approach to harmonizing this understanding and developing a common vocabulary and classification. However, business units may be allowed some leeway. You can learn more through Fortinet.
Issues
While most data management processes are governed by legislation, several essential issues exist, especially concerning data stewardship. In a nutshell, data governance lays the groundwork for collecting and handling data, establishing processes for decision-makers to manage data, and ensuring data security against outside forces. Briney, K. (2015). Data management for researchers. Exeter: Pelagic Publishing.
When implementing a Data Governance program, IT and business leaders should be on the same page when discussing systems and platforms. IT and business leaders should work together to define data, produce high-quality data, and use that information for operational purposes. Regardless of the role of each department, there must be agreement among all groups that the program is necessary. It should be budgeted and owned by the business, as well. When adequately executed, Data Governance can help companies to improve their performance and competitiveness.
Goals
The goals of data governance are several and varied. For instance, data consumers care about the availability of data and its accuracy. Metadata analysis and browsing of related metadata objects are also critical. Data users also care about the authenticity of data. By adopting a data governance strategy, you can meet these needs. Once you have decided to implement it, there are many steps you need to take.
Data governance improves business performance. It improves data quality, resulting in better interactions with customers. Higher quality data is necessary for better decisions, resulting in increased revenue and competitive advantages. Effective data governance helps you make better business decisions. By implementing effective data governance, you can expect to reap many benefits. But ensuring high-quality data is not enough. Your goal should be to make data-driven decisions. For these goals, you need to set goals, KPIs, and measures that will enable you to measure success.
Processes
Traditional data governance processes involve the tedious manual discovery of data assets and lack a centralized place to register metadata. Data assets are not visible to users until they are actively used. Furthermore, the data may be stored in multiple formats and types, with little or no effort to organize or catalog it. Hence, traditional data governance setups are less likely to deliver the benefits that Data Governance promises.
Data Governance includes the establishment of target-oriented organizational forms and effective processes. A vibrant Data Governance depends on having the “right” people. To develop the necessary procedures and policies, hiring skilled individuals with the relevant skills to fulfill these roles is imperative. In addition, data governance requires skill profiles that combine business and IT know-how. Once defined, the skill profiles help create a balanced mix of organizational skills. Data governance also involves determining the “right” people for each position in the organization.
Costs
There are several costs associated with data governance. The first is the initial investment. Choosing a cloud-based solution will allow you to avoid capital expenses and treat them as operating expenses. You will also benefit from superior pricing, as the cloud provider matches storage capabilities to real-world usage. In addition to these costs, cloud-based data governance solutions will provide many of the same benefits as traditional solutions. These benefits include robust analytics, a secure audit trail, and reduced support costs.
The following cost associated with data governance is the time and resources needed for proper implementation. Data governance takes a lot of time and effort and may require dedicated staff. However, with the appropriate performance, you can recoup the investment, as high-quality data will allow you to streamline business processes and determine consumer needs. And, with a successful data governance plan, you can reap the benefits of data-driven decisions. You will also gain a clear understanding of data rights and privacy laws.
Implementation
To implement data governance in an enterprise, start by engaging the appropriate stakeholders and building a change network. The change network can serve as a pilot audience for the more comprehensive effort. In addition, key individuals can define preliminary processes and general approaches you can refine. These steps can help establish the need for data governance within the organization and build team priorities.
Identify the critical data. Then, create policies and standards for governing essential data. Implement a plan that focuses on the most critical data elements. Define the metrics for controlling the quality and access of data. Then, determine the impact of data governance on different business-related tasks. Data governance can help ensure the security and accessibility of data and improve employee satisfaction. It’s also essential to consider the impact of data management and analytics on an organization’s bottom line.
