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PPTs – Chapter 5 – Data Governance

DG recognizes data as a corporate asset requiring the same priority for management as other high stake organizational assets. DG is an enterprise-wide effort that requires a high-level priority, similar to the management of other corporate assets, and needs executive sponsorship and support to succeed. DG is an iterative process. Initial efforts should be small steps that focus on top mission priorities that quickly deliver value and expand as the program matures.

DG is both strategy and management. From the strategy perspective, DG must be linked with major business drivers and organizational strategic goals and be supported by a business case. These determine the portfolio of DG initiatives the organization will undertake. From the management perspective an organizational structure and communication, measurement, and control processes need to be put in place.

DG is a team and collaborative effort requiring participation from all levels of organizational stakeholders. A DG program’s decision-making design can be centralized or decentralized. Coordination of decision making can take either a hierarchal or cooperative approach, depending upon organizational culture and current management structures. DG specifies who has the authority and accountability for data decisions and who is responsible for carrying out the activities associated with these decisions. This requires identification and codification in written documents of the priorities, goals, main activities, roles, and responsibilities that are undertaken.

Customary roles associated with a DG program include an executive sponsor, a high-level and strategic and oversight committee, and data stewards including a chief data steward, and business, and technical stewards. The DG program is usually supported by a DG office, headed by the chief data steward or other senior data management professional. Typical functions include facilitating and coordinating meetings of data stewards, providing administrative support to DG councils and committees, collecting and reporting metrics and success measures to data stakeholders; providing ongoing communications, record-keeping, and education for the DG program; providing centralized communication for DG initiatives and projects; collecting and archiving; and serving as liaison to other data or information-related functional areas such as Data Quality, Compliance, Privacy, Security, and IT.

Core disciplines in a DG program may include information life cycle management, data quality management, information security and privacy, master and reference data management, metadata management, data architecture management, data development, and business intelligence management. Common DG processes include aligning policies, requirements, and controls to strategic organization and DG goals; establishing decision rights and accountabilities; managing change; defining data; resolving data issues; specifying data quality requirements and metrics; establishing baseline data quality status; measuring and reporting data quality; establishing communication and reporting avenues; and performing stewardship activities such as measuring and reporting data quality, defining data requirements and definitions, and implementing policies, processes, and controls.

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