Data Governance Program

In alignment with the strategic priorities of the University of British Columbia, the Data Governance Program creates the foundation to enable students, faculty and staff to make data driven decisions with measurable outcomes.

Guiding Principles | Objectives | Framework

Guiding Principles

  1. University data is a key strategic asset to UBC and therefore is managed appropriately throughout its lifespan.
  2. University data is easily accessible to relevant members of the UBC community as needed in order to carry out their roles.
  3. Quality standards for University data are defined and monitored. University data is trustworthy.
  4. All members of the university community own an equally important role on ensuring they are compliant with data governance procedures and standards.
  5. Resolution of issues related to quality and accessibility of university data follows consistent processes.
  6. There is a common vocabulary and shared and approved data definitions.
  7. There is a single version of truth for university data and primary sources of information will be updated with the most current information.
  8. University data is not unnecessarily duplicated and satellite databases are not created in an effort to achieve System of Record.
  9. University data management must comply with legal requirements and privacy and security principles, both internal and external.

Objectives

  • Develop and implement data management policies and standards that are consistently applied.
  • Educate the university’s community on how data enables strategic decision-making – linking data to strategic outcomes.
  • In partnership with Privacy and Information Security Management (PrISM), support proactive monitoring and mitigation of privacy and information security risks while facilitating data accessibility.
  • Develop a culture of sharing data and a common understanding of the value of data to measure progress and inform plans.
  • Foster automation of business processes by ensuring trustworthy and usable data is available.
  • Establish the foundation for an analytics program for Teaching and Learning, Research and Administration that enables data driven decision-making.
  • Lead the development of standard definitions needed to ensure data quality.

Framework

The vision of the Data Governance Program is to deliver:

"High quality and accessible data to advance UBC's purpose and vision delivered by integrated data management and principled governance".

Data Governance Framework

The main pillars of data governance for UBC are:

Policies, Guidelines & Standards

Policies, standards and guidelines can be described as the “Rules of Engagement”. Most of these are focused on controlling the behaviour over the definition, production, organization, and use of information.
This pillar helps determine who has authority to make decisions regarding access, priorities, data standards, and the conditions under which these decisions can be made.

Data Quality Framework

The Data Quality Framework is based on various industry standards. It is an iterative process, developed to enable UBC community to partner and collaborate in order to obtain true value and achieve the benefits of good quality data. Data quality is a fundamental requirement to enable data informed decisions. UBC leaders require reliable consistent and coherent data to ensure appropriate informed decisions can be made. An integrated approach that supports a culture of data quality and engagement of faculty, students and staff is required to meet the information needs of the UBC community.

Privacy, Compliance & Security

How UBC manages the inherent risk that comes along with collecting sensitive data is an essential part of the data governance program. Developing the risk management strategies and making those operational are under the purview of the program. Additionally, compliance with record retention policies for differing record types. The Data Governance Program should align with and coordinate with records management to ensure compliance.

Information Architecture & Integrations

Ensuring that there are common data definitions and that those definitions are made available across multiple platforms is essential to enabling informed decision making. Common data is used to describe existing and future capabilities of the institution, formulate a sustainable information architectural ecosystem, and guide institution-wide data integration. Decisions on what those definitions are and how the requirements of those definitions are technically supported is a part of the program.

Reporting & Analytics

Just as contractors would never build a house without clear blueprints, analytics teams need data governance to guide and structure their most important activities. Data governance informs everything from analytics software implementation to page tagging to report design. Synonymous with “quality control,” data governance strives to ensure the university will have reliable and consistent information to assess performance and make management decisions.

All the pillars in the Data Governance Framework are enabled by:

People, Processes and Technology

Effective governance is not a one-time exercise, but rather a fully developed effort and repeatable process – executed by people and supported by technology. Governed and principled management of data, are the only way to ensure ongoing compliance with institutional standards and requirements, and data integrity in light of future changes (such as evolving business challenges, emerging technologies and new data flows).
It is through principled data management that UBC can achieve trusted data. It is about working together on fixing and preventing issues with data in order to make data driven decisions. Data governance also describes an evolution to a new paradigm in the institution’s way of thinking to avoid silos of data and make information available institution-wide. It is about using technology to support the business processes.