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Data Governance Committees

The accordion below outlines the three committees, their primary responsibilities, and one-year goals.

Primary Responsibilities
  • Review and revise data handling policies, standards, and guidelines.

  • Coordinate data-related Web Certification processes.

  • Collaborate with information owners and as necessary, privacy and security officers, to ensure appropriate data access and sharing authorization and review processes are in place.

One-Year Goals
  • Reformulated representative committee, including regional campus representatives. 

  • Review and revise data handling policies, standards and guidelines (includes shoring up definitions of each data class).

  • Coordination of data-related web cert processes in place.

  • Data Cookbook work in progress documenting the classification of data fields.


  • Document best practices and recommendations for:

    • Creation and updating content

    • Review and evaluation of new software features

    • Review of current quality tracking processes including risk assessment, issue resolution

  • Identify market segments / personas (user profiles)

  • Determine a common lexicon that describes our data environment. What does it mean to be standard content, official, native reporting, warehoused?

  • Represent needs of end users (operational decision-makers, executives)

    • Ensure information is consistently available, accessible to support business needs

    • Create avenues to request assistance, report data issues, access community resources 


  • Define markets segments / personas (user profiles) for those who commonly access enterprise data and the tools they generally use

    • Connect user profiles to appropriate solutions

    • Review current content (focus on Cognos and Tableau) through the market segmentation (user profile) lens. Identify opportunities, best practices

  • Generate and disseminate definitions for various types of content (departmental, standard reports, official reports, and validated reports; Landing Page)

  • Identify decision tree for:

    • Where content should be housed (Data Digest, Management dashboard, Cognos)

    • Data tool selection based upon purpose, benefits, limitations

    • Process for determining resolution of quality issues, including data issues in reporting environment versus operational system

  • Create documentation/matrix of where to go for to find information to eliminate errors when pulling data from wrong source

  • Ensure data quality process in place for each major data segment (discover, track, resolve)

Primary Responsibilities
  • Create a communication framework and templates in conjunction with each data governance committee. Each committee will share updates on standards, processes, procedures successes, goals. 

  • Provide change management guidance/expertise to other data governance committees.

  • Establish training and communication standards, best practices, and processes.

One-Year Goals
  • Formulate communication standards, templates and processes for the Data Governance committee chairs.

  • Partner with Data Stewards to communicate and co-ordinate training once they determine what is mandated.

  • Create a strategic Training Roadmap, to include a recommendation of prioritized training needs, scope and sequence (based upon audience training assessment), and best practices for development and implementation.

  • Identify and prepare a recommendation of subject matter experts and departmental resources required to co-ordinate and support the Training Roadmap.  

  • Coordinate the addition of completed training content into the LMS from across multiple functional areas.

  • Promote additional LMS functionality needed for training, data literacy.

Data Governance Committees Directory

Early in 2022, a multi-departmental working group, led by Molly Amstutz, chief data officer, formed a recommendation for a data governance committee structure. Five data committees were approved by the Executive Data Council (EDC) in March 2022. An evaluation of the 1-year goals for the committees led to the EDC approving two recommendations in fall 2023. 

  1. Merge the Content Stewards, Data Quality, and User Experience Committees into one new entity. The newly formed Quality Data Experience committee allows us to realign for greater efficiency and lower redundancy and duplication of effort. The Training and Communication committee and Data Stewards committee will remain intact as separate committees. 

  2. Establish an Active Member and Advisory Member status for committee members. It was recommended to revise the roles and responsibilities of committee members to better leverage expertise and maximize output. All committee members play a vital role in advancing data governance and therefore their input and feedback are highly valued.  An Active Member will meet on a regular basis with the committee and will work to co-create solutions by consulting with peers, collecting information, and actively engaging in committee work.  Advisory Members will offer guidance when solicited and provide additional insight on content drafted by active members.  The committees will maintain an enterprise view involving cross-functional representation, while making better use of all members' time. 

Overarching support of this data governance framework is provided by the chief data officer and the institutional data governance program manager. The framework focuses on collaboration across reporting systems. The committees consist of staff from finance, human resources, research, student, academic colleges, administrative operations, and other related areas. Joining the expertise of those who report from Ellucian Banner with those who report from SAP ensures consistency and standards for the data community. By working in coordination rather than in parallel, it provides risk management and lessens the barrier that the data community has in navigating Banner and SAP data.

While many of the responsibilities of these committees are currently occurring, this structure will increase efficiency and quality. The standardization and sharing of expertise provide a service to the data community and University. It supports large cross-departmental projects and major initiatives. It also provides data staff with mentoring and career development.