David wishes to thank Anne Marie Smith, director of Education at EWSolutions, for her invaluable contribution to this month's column.
As government-mandated regulatory requirements and the need for enterprise-wide data analysis continue to grow, many companies and large government entities are looking to attain standard definitions for their common data. Not surprisingly, these same organizations have come to the realization that a managed metadata environment is necessary to persistently store and technically manage those definitions; however, it is only half of the equation. There is also a business side to defining the processes and procedures necessary to initially create and manage these common data definitions on an ongoing basis. These processes and procedures are known as data governance and stewardship.
Data governance and stewardship provide tremendous value to an organization, as they can help your company:
- Understand the quality of your common data,
- Provide a path to improve the quality and accuracy of your common data,
- Identify and consolidate the redundancy in your common data,
- Identify what costs your organization incurs by having duplicate data,
- Provide a clear understanding of who is responsible for your data,
- Identify the costs for not having standard definitions of common data,
- Define the business rules and valid domain values for your common data,
- Discover where business rules and valid domain values are not being followed,
- Enable master data management, and
- Provide a defined and sustaining feedback loop to continuously improve your data.
There are many definitions of data governance. One that has resonated well with many organizations follows:
Data governance is the practice of organizing and implementing policies, procedures and standards for the effective use of an organization's structured/unstructured information assets. Data governance is accomplished through the actions of data stewards who exercise the careful, responsible management of data entrusted to them on behalf of others.
The data governance framework includes the intersection of and relationship with data quality, metadata management and master data management (MDM) for a comprehensive information management strategy administered by data stewards. (Note: owners and stewards are not interchangeable. Owners have power and control; stewards manage on behalf of the owner, perhaps without control over the resource/object.)
Data Governance Benefits
Data governance helps you control valuable data and information assets and assists you in making more effective use of the assets. The realization of data as a valuable and manageable organizational asset is one of the main business benefits of a data governance initiative. Most enterprises carefully manage other assets (financial, physical and human) but overlook the immense value inherent in their data. Other business benefits include a reduction in data redundancy, improved business decisions due to accurate data from the recognized source of record, shorter time to compile data for business decision-making as well as increased user trust in data stored within the organization's databases.
Governance plays a fundamental role within MDM. Typically, if an organization is cognizant of the data it captures, stores and uses, it is only aware of the deficiencies of that data and not the many ways that data can be transformed into valuable information. Instituting a data governance program as part of an MDM effort will provide a company with a central focus for identifying and controlling the collection, storage and disposition of information resources.
In many organizations, information architecture consists of numerous applications and databases that are in many formats, some integrated and others (the vast majority) in lonely silos. With little or no documentation of the trusted sources of data and the relationships among applications that capture and use data, many data consumers have difficulty identifying the right data for their needs and are not certain of the quality and currency of the data they have. These problems indicate a lack of data governance and stewardship, which can lead to serious financial, regulatory and legal ramifications should workers use poor quality data for business decisions or if access to critical data should be restricted for privacy or other reasons. Without data governance, adhering to these regulations could become difficult and maybe impossible in large organizations. A data governance program encourages the understanding and management of data from both business and technical perspectives, plus it promotes the importance of data as a valuable resource, allowing the organization to use its data confidently to satisfy regulatory and other business needs.
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