Data governance

Data governance is a quality control discipline for assessing, managing, using, improving, monitoring, maintaining, and protecting organizational information.^[1] It is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.^[2]:

[edit] Overview

Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise, including the goals of:

• Increasing consistency and confidence in decision making
• Decreasing the risk of regulatory fines
• Improving data security
• Maximizing the income generation potential of data
• Designating accountability for information quality

These goals are realized by the implementation of Data governance programs, or initiatives.

[edit] Data governance initiatives

Data governance initiatives improve data quality by assigning a team responsible for data's accuracy, accessibility, consistency, and completeness, among other metrics. This team usually consists of executive leadership, project management, line-of-business managers, and data stewards. The team usually employs some form of methodology for tracking and improving enterprise data, such as Six Sigma, and tools for data mapping, profiling, cleansing, and monitoring data.

Data governance initiatives may be aimed at achieving a number of objectives including offering better visibility to internal and external customers (such as supply chain management), compliance with regulatory law, improving operations after rapid company growth or corporate mergers, or to aid the efficiency of enterprise knowledge workers by reducing confusion and error and increasing their scope of knowledge. Many data governance initiatives are also inspired by past attempts to fix information quality at the departmental level, leading to incongruent and redundant data quality processes. Most large companies have many applications and databases that can't easily share information. Therefore, knowledge workers within large organizations often don't have access to the information they need to best do their jobs. When they do have access to the data, the data quality may be poor. By setting up a data governance practice or Corporate Data Authority, these problems can be mitigated.

The structure of a data governance initiative will vary not only with the size of the organization, but with the desired objectives or the 'focus areas' ^[3] of the effort.

[edit] Implementation

Implementation of a Data Governance initiative may vary in scope as well as origin. Sometimes, an executive mandate will arise to initiate an enterprise wide effort, sometimes the mandate will be to create a pilot project or projects, limited in scope and objectives, aimed at either resolving existing issues or demonstrating value. Sometimes an initiative will originate lower down in the organization’s hierarchy, and will be deployed in a limited scope to demonstrate value to potential sponsors higher up in the organization.

[edit] Data governance tools

Leaders of successful data governance programs declared in December 2006 at the Data Governance Conference in Orlando, Fl, that data governance is between 80 and 95 percent communication.”^[4] That stated, it is a given that many of the objectives of a Data Governance program must be accomplished with appropriate tools. Many vendors are now positioning their products as Data Governance tools; due to the different focus areas of various data governance initiatives, any given tool may or may not be appropriate, in addition, many tools that are not marketed as governance tools address governance needs.^[5]

[edit] Data governance organizations

The IBM Data Governance Council ^[6]

The IBM Data Governance Council is an organization formed by IBM consisting of companies, institutions and technology solution providers with the stated objective to build consistency and quality control in governance, which will help companies better protect critical data."

The Data Governance and Stewardship Community of Practice (DGS-COP)^[7]

The Data Governance and Stewardship Community of Practice is a vendor-neutral organization open to practitioners, stakeholders and academics, as well as vendors and consultants. The DGS-COP offers a large collection of data governance artifacts to members including case studies, metrics, dashboards, and maturity models as well as on-line events.

Data Governance Conferences^[8]

Two major conferences are held annually, the Data Governance Conference, held in 2008 in San Francisco, CA, USA, and the Data Governance Conference Europe, held in 2008 in London, England.

Master Data Management & Data Governance Conferences^[9]

Six major conferences are held annually, London, San Francisco, Sydney and Toronto in the spring, and Madrid, Frankfurt, and New York City in the fall. 2009 is the 4th annual iteration with more than 2,000 attendees per year receiving their data governance and master data management updates via this 2-3 day event.

[edit] See also

• Information technology governance
• Master Data Management

[edit] References