A data strategy is a comprehensive, integrated, strategic approach to data management and governance for an enterprise. It utilizes guidelines, procedures, and technical documentation for collecting, managing, and sharing data to make it reliable (i.e. data is accurate, clean, and usable). Data strategies may include one or more of the following approaches:
In its most simple form, data strategies may involve only the implementation of processes that directly affect the data's quality. More complex data strategies require the identification and evaluation of multiple perspectives that influence an organization's data quality, as well as the collection and dissemination of that data. The resulting approach, a data governance strategy, is a more complete and often more complex set of processes and policies. In addition to affecting the quality of data, a comprehensive data strategy can also serve to guide and direct activities related to the organization's data, such as data accessibility, the storage and access to data, the sharing of data, maintenance of data integrity, usage management, security, access control, use of data in regulatory and public policy efforts, workflow development, and more.
Each aspect of a comprehensive Data Scalability addresses one or more business objectives. A business objective is a result you want to achieve from your data strategy. Common business objectives are increasing customer value, reducing cost, improving product or service quality, increasing employee productivity, increasing sales, and increasing market share. At a minimum, all business objectives must be considered in the data strategy.
Data governance strategies must take into consideration the types of analytics the business will conduct. Typically, businesses begin by evaluating the information technology and competitive advantages of their existing data management system. The purpose of an evaluation is to determine which of the available solutions best suits the business's needs. The resulting data strategy then addresses the different analytical needs of each company.
While all of these things are important, there are specific goals that must be addressed by an organization's data strategy and governance process. One of these goals is to improve internal organization effectiveness. Other goals related to organizational effectiveness include increasing employee and organization productivity, reducing financial risk, increasing customer satisfaction, meeting regulatory requirements, fulfilling legal obligations, achieving organizational mission goals, and more. In each of these cases, a comprehensive strategic framework must be in place.
The third factor that affects an organization's data strategy and governance process is the type of users that will be permitted to access the information. Depending on the nature of the users, an organization's Generic Data strategy will vary. For example, in an enterprise setting, users may include owners, managers, employees, suppliers, and others. Therefore, a comprehensive data strategy and governance solution must address the needs of any user that will be accessing the organization's data. Long-term goals must also be included in the strategy and the implementation of those goals should be included as part of the strategy. You can get more enlightened on this topic by reading here: https://en.wikipedia.org/wiki/Data_governance.
