Several years ago I worked on a set of core Data Governance Principles with a client in the U.S. with headquarters in Europe. The principles that we came up with represent a simple view of what his organization set out to accomplish by deploying a formal Data Governance program. The intent and hope was that we would get the highest level of the organization to agree that these principles were extremely important and that actions must be taken to accomplish what they state. It may have been a pipe dream, but we were also hoping that senior management would sign a policy statement of which the foundation of the policy was the principles.
The resulting principles have become something I have used in many of my presentations and webinars. It is my thought that organizations should consider these principles as an easy way to describe the basics of Data Governance for their organization.
From time-to-time TDAN.com republishes articles as Special Features. This article, an excerpt from Seiner’s book, Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success, was originally published in TDAN.com in 2012 and in the book in September of 2014. The article was well-received then and quickly outlines Data Governance Core Principles.
The Principles
The Core Principles that we came up with were:
- Data must be recognized as a valued & strategic enterprise asset.
- Data must have clearly defined accountability.
- Data must be managed to follow internal & external rules.
- Data quality must be defined & managed consistently across the data life cycle.
The graphic below shows how a policy can break down into principles that are supported by dimensions of data quality. The graphic includes Tag Lines (a quick phrase to help remember each principle) in bubbles attached to each principle.
1. Data must be recognized as a valued & strategic enterprise asset.
Tagline – From “My Data” to “Our Data”
Rationale:
- Data comprise a valuable corporate resource. Accurate, timely data are the critical foundation for effective decision-making and customer service at the company.
Implications:
- Carefully manage data to ensure they are clearly defined, properly accessed, and appropriately controlled. Company management and staff must be able to rely upon the accuracy of data and be able to obtain data when and where needed.
2. Data must have clearly defined accountability.
Tagline – Data Governance is “Everyone’s Responsibility”
Rationale:
- Most data has value to the organization beyond the uses of any one specific application. A company requires that data be shared and integrated at the enterprise level, consistent with information security and privacy policies (see relevant policies).
- Data must be well defined to be sharable. Enterprise-shareable data must be defined consistently across the Enterprise, with understood definitions available to all users.
- Wide access to data leads to efficiency and effectiveness in decision-making, and provides timely responses to information requests and service delivery.
Implications:
- Shared data will result in improved decisions. It is less costly to maintain a single source of timely, accurate data than to continue to maintain several sources of data that are not unique. Data will be better aligned with cross-business requirements, syntactic and semantic differences between databases will be minimized, and applications will be more portable. Additionally, Data Management can change the data environment based on changing requirements or conditions with a minimal impact to the applications.
- Data must be protected from unauthorized use and disclosure. Processes, procedures, and automated methods will be used to ensure the security of data.
- Access to data should be performed through appropriately defined interfaces to ensure the proper understanding and use of the data.
- To enable data sharing, the Data Governance Team with the cooperation of the Data Domain Stewards and the business areas must develop, abide by, and communicate a common set of definitions, policies, and standards. Common data definitions are the foundation for systems interfaces and data exchanges. A common vocabulary will increase the value of the definitions.
3. Data must be managed to follow internal & external rules.
Tagline – Avoid Risk & Compliance Issues
Rationale:
- Current legislation and regulations require the safeguarding, security, and privacy of personally identifiable information.
- Open data sharing, managed accessibility, and the release of data and information must be balanced against the need to restrict the availability of restricted, proprietary, or sensitive information.
- Data Owners, in the role of Data Domain Stewards, are accountable for data quality, definition, security, privacy, standardization, and the appropriate use of data in their domain.
Implications:
- To improve the quality and value of data, and to avoid risk and compliance issues, accountability and rules for the definition, production, and use of the data must be recorded, managed, and communicated.
- The Data Governance Team must be responsible for recording and communicating information about individuals’ accountabilities across the company.
- The Data Governance Team must work with the business areas to assure that the relevant regulations are documented and communicated to impacted areas.
4. Data quality must be defined & managed consistently across the data life cycle.
Tagline – Right the First Time, Every Time
Rationale:
- The quality standards for data must be well defined to be able to identify, record, measure, and report the quality of the data.
- The quality standards will focus on measuring business process and decision-making improvements from complete, relevant, and unique data.
- Enterprise-critical data must be tested against the standards consistently across the Enterprise, with understood standards available to all data definers, producers, and users.
- Data Owners, in the role of Domain Stewards, are accountable for data standard definitions and appropriate use of the standards for data in their domain.
Implications:
- To improve data quality, the Data Governance Team, with the cooperation of the Data Domain Stewards and the business areas, must develop, abide by, and communicate a common set of standards.
- Common data standards are the foundation for quality systems interfaces and data use. A common place to record data standards will increase ability to improve the quality of the data.
I have heard it said that a picture is worth a thousand words. I have been told by people attending my presentations and webinars that the picture of the principles falls in that category.
The truth is, the simpler we stay with our concepts around Data Governance, the easier it is for people in our organizations to understand what Data Governance will achieve for the organization. Please feel free to use the basic principles I described in this article or come up with your own as a simple way of describing the mission of a sustainable Data Governance program.
