Data Governance and Stewardship in Enterprise Data Management
Data governance. What is it? Why is it important? What is the relationship between governance and stewardship? Does enterprise data management need data governance? These questions, and others, are asked and answered daily by individuals and organizations that are searching for a way to address the need to understand and use their data more effectively and provide greater accountability for the capture, storage and usage of data. Governance and stewardship are critical subjects that all organizations should start to examine before they discover that their data is uncontrollable.
Governance plays a fundamental role in an enterprise data management approach. An enterprise management program is designed to emphasize the importance of managing information as an asset. Most enterprises carefully manage other assets (financial, physical, and human) but overlook the value inherent in their data. 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 turned into valuable information. Instituting a data governance program as part of enterprise data management practice 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 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 financial and legal issues should workers have access to poor quality data for decisions or have access to data that should be restricted. Data quality standards have been mandated by the 2002 Sarbanes-Oxley Act. SOX requires, among other things, that organizations attest to the quality of the data contained in their financial reports. Regulations also concern the safety and security of personal data, requiring companies to demonstrate that they have proper controls established to limit access to sensitive or personal data. Without data governance, adhering to these regulations could become difficult. Enterprise data management optimizes the use of the corporate data assets for both the business user and the IS community. Having a data governance program encourages the understanding and management of data from both business and technical perspectives and promotes the importance of data as a valuable resource, allowing the organization to rely on the data that it uses to satisfy regulatory and other management needs.
There are many definitions of data governance and data stewardship. One that has been accepted by 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 acts 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, meta data management, and master data management 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).
Benefits of data governance include enabling the organization to produce high-quality information which is useful, appropriate, and timely by:
- Providing one point of accountability
- Reducing data duplication
- Increasing confidence in data
- Improving timeliness and usability of data
- Establishing a common vocabulary of data to ensure access to the right information
- Defining enterprise-wide (or site / project wide) values for common reference data
Frequently, data governance and stewardship are thought to be part of a data quality process, and a data quality project is one way to bring data governance into an organization’s focus. Information quality is a measure of how well the business information demand is met. It is the ability to get the right data, to the right people, in the right place, at the right time, in the right form, at the right cost, so they can make the right decisions, and take the right actions. Data resource quality is a measure of how well the data resource supports the current and future business information demand, providing the right data to support information quality. “Data resource quality” can be called “meta data quality” and the role of data stewards includes attention to the quality of the meta data for the data under their stewardship.
Since each organization is unique, one could argue that there are as many data governance methods as there are organizations implementing this process. Nevertheless, certain points are universal in governance and can be used to examine any methodology / process.
Sponsorship and commitment to the goals of data governance and the processes to implement it should be foremost. Lack of senior management commitment has killed many governance programs and doomed many data stewards. Analyzing the organization’s culture is also very important: can data governance become part of this organization’s culture? Will standards be applied equally across the organization? Can the organization sustain governance and can stewards be empowered to perform consistently? Will the organization allot sufficient funds to execute and maintain the governance strategy and stewardship functions? Does this organization have an enterprise view of data that would foster the development and maintenance of a data governance program? Can management make the changes necessary to “do” data governance properly?
Technology provides the way to manage and deliver data for the users / consumers. Therefore, choosing the right set of products is essential for a successful data governance program. This includes databases, Enterprise Application Integration and Extract, Transformation and Loading tools, meta data management and master data management products, data quality tools, and data warehousing / business intelligence products. The abundance of technical options means that an organization also must develop a plan to choose the right ones for their needs. The organization also must plan to integrate these tools and the processes that they serve to support data governance objectives.
Process development is the core focus for data governance. Processes for governance include coordinating, managing and monitoring the development and use of organizational audit and control procedures and data standards and policies. One critical area involves managing meta data standards, since meta data allows the organization’s ability to understand its data sources, definitions, uses and relevance. All data standards and policies should be part of the data governance program, so policies are consistent and changes can be sent throughout the organization when necessary.
Two groups with responsibility for an organization’s data governance program are the Data Governance Council and the Data Stewardship Team. A Data Governance Council:
- Coordinates and directs data governance strategies and processes across the enterprise
- Ensures that data governance strategies and processes support the organization’s mission and objectives
- Develops and directs data standards across the organization and within projects
- Assigns roles, responsibility, and authority and implements governance through a number of organizational layers
- Provides mechanisms for coordination, communications, information sharing, prioritization, and conflict resolution within the organization and across projects
- Provides accountability for the successful implementation of all governance efforts, whether at the enterprise level or within lower organizational levels (division, group, project, etc.)
Data stewards are the glue that holds a governance program together. Stewards:
Define subject area boundaries in conjunction with IT and business leaders
Collect feedback and enhancements for specific subject area
Resolve data integration issues
Act as the conduit between business and IT
Serve as quality control point for the subject area
In the context of their defined subject area domains, data stewards:
Define / describe business data elements
Define data domain values
Establish and validate data quality rules
Identify and help resolve data quality issues
Help develop data domain business rules (algorithms, calculations, processing requirements, etc.)
Define security requirements
Data Stewards for each functional area should be identified and given training in the basics of data and meta data management. The Governance Council sets the standards for the data and meta data that is appropriate for their organization, and stewards are an integral part of a data governance council. The Data Governance Council should be involved in all IS application activities (package evaluation and implementation, application development and maintenance) to manage the impact the activity will have on the integrity of the data under their stewardship.
In the final analysis, data governance is a complex topic and one that should be examined carefully before developing your organization’s program. Having the services of an experienced group of information management professionals can make the difference between a successful data governance program and a failed one.