HomeStrategy and Future DeptOffice of Institutional Research and Data AnalyticsZU Data ManagementData Governance

Data Governance


What is Data Governance?

Data Governance

Data governance (DG) is the exercise of authority, control, and shared decision making (planning, monitoring and enforcement) over the management of data assets. At ZU, data governance ensures data consistency, reliability, and a single source of truth. Data governance is iterative, and it is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models.

Key Objectives of Data Governance at ZU

  • Centralized Data Library: Establishing a central repository for all university data.

  • Data Governance Framework: Implementing a framework to manage data effectively.

  • Data Quality: Ensuring data accuracy and consistency.

  • Data Classification: Implementing protocols for data classification.

  • Advanced Analytics: Integrating advanced predictive analytics.

  • Self-Service Reporting: Providing self-service capabilities for ad-hoc reporting.

  • Efficient Data Processing: Speeding up data processing and minimizing manual handling.

  • Democratized Data Access: Ensuring that all data is accessible from one platform.

  • Compliance: Adhering to standards from regulatory bodies such as TDRA, MOE, PMO, ADEK, and CAA.

Key Components of Data Governance

  • Data Catalog: Provides complete visibility of the data landscape by pulling metadata to a central location, enabling users to discover and understand data.

  • Data Lineage: Tracks the source of data and its evolution, ensuring data comes from trusted sources.

  • Data Security: Enforces access restrictions and protects sensitive data through encryption and masking.

  • Data Quality: Performs data profiling and installs data quality checks, ensuring the accuracy, completeness, and consistency of data.

  • Business Glossary: Defines key business terms and concepts, ensuring consistent understanding across the university.

  • Data Classification: Organizes data into categories based on sensitivity (Restricted, Confidential, Internal, and Public).

  • Policies and Procedures: Provides guidelines for managing the data lifecycle.

  • Master Data Management (MDM): Creates a uniform set of data across different systems.

Data Governance Committee (DGC)

The DGC is a key decision-making body responsible for ensuring effective data management, quality, security, and privacy.

The DGC:

  • Sets priorities for data governance.

  • Establishes data classification categories.

  • Approves access to reports.

  • Reviews and approves the Business Glossary.

  • Approves data governance policies.

  • Comprised of members from various departments including senior leadership, academic representatives, and directors.

  • Regulates data governance per data subject area.

Data Owners and Data Stewards

  • Data Owners are individuals or groups within departments who oversee data management, security, and quality and are accountable for upholding the accuracy, integrity, and security of data.

  • Data Stewards possess subject area expertise and contribute to data management and technical challenges; they maintain and enhance data quality. They enrich business glossary terms and their supporting information.

  • ZU has identified data owners and stewards for various departments.