Data Governance

Data governance means taking a structured approach to managing data to achieve improved  accuracy, completeness, consistency, validity, timeliness and uniqueness. The University is working towards this through the creation of its Data Governance Framework and delivery of its Data Strategy.

The sections below outline the key elements of the University’s efforts to establish data governance for its administrative data.


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The University has complex and interdependent data flows between its administrative data systems with many teams involved through the lifecycle of those data. The data include: 

  • finance data
  • student data
  • staff data
  • estates data
  • research data
  • development and alumni relations data

It is important to know who to involve when data issues are identified and to know what different teams can expect of each other.  A consistent model of roles and responsibilities for the quality of the University's administrative data is still in development but the following groups have been established to take collective responsibility for driving good practice:

  • Data Executive Group  carries out the following activities:
    • setting policy, accountability and responsibility for the University’s adminitrativedata
    • continually assessing the University's ability to meet external requirements and reducing risk (regulatory and statutory), whilst fully exploiting its data assets for decision-making and providing support for strategic objectives
  • Data Governance Group  works with the Data Governance Manager and others to develop, implement and maintain an appropriate Data Operating Model.  It aims:
    • to ensure that the Data Operating Model, and key data governance and quality activities, provide clarity for everyone who is working with their data, as an analyst, report-writer or consumer of that data
    • to facilitate greater accuracy, confidence, and efficiency in data reuse, reporting and decision-making

The University's Data Assurance Group  continues alongside these with a focus on assuring the University's external data returns.

Due to the inter-connected nature of our data systems and processes, we need tools and techniques that, when applied, will help to:

  • ensure we understand the data we are using
  • ensure that we are using the right data for the purpose
  • enable us to be consistent and accurate when entering and using data

The Data Governance Framework will provide tools and techniques for this including but not limited to:

  • a data issues reporting form for use when other channels are not available or unclear
  • establishment of the data issues log where information about reported issues is recorded for ease of monitoring progress to resolution
  • data quality training module  
  • the Casewise database, which includes details of agreed data definitions, sources and contact names, and is available to all staff with SSO. You can find out more, and access the database, via the Enterprise Modelling SharePoint site  
  • support to define data standards and develop data quality checks