Executive Summary
This document outlines the Data Governance
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Within this draft, framework for Sequoias CCD, emphasizing the structure, guiding principles, and roles and responsibilities essential for effective data management and decision-making across the district.
This work is in response to District Objective 4.1 which is to increase the effective use of data and transparency in decision-making at all institutional levels from 2021 - 2025.
Action item 4.1.1 - Improve Data Governance practices, including the establishment and publication of clear definitions, responsibilities, and roles as well as data access, data entry, methodologies, and validation/correction protocols.
Action item 4.1.2 - Establish and publish procedures to ensure constituents know where to find needed data, have access to all relevant data, and ensure the data is regularly updated.
Working with the above as a guide, College of the Sequoias is embarking on a new chapter in managing data and supporting data informed decisions. We are doing this by taking good ideas from the past and building upon them with new modern architecture to bring about a governance process that ensures the right people are at the table in making decisions about data definitions, policies, usage, and maintenance. In addition, putting a process in place to discuss, track, and approve changes in definitions, coding structures, and data usage in a way that is useful for the institution, supports transparency, and is not overly burdensome.
Organizational Structure
Data Governance is a process that would require a group to be formed that would report to the President or designee and function as an “Operational Group” as defined in the 2022 COS Governance and Decision-Making handbook, page 11Manual.
This group would be called the Data Management Council.
Guiding Principles
Inspired by (Hopper, 2022) and (Meteyer, 2021)
Data Accuracy and Integrity:
Principle: We prioritize the accuracy, consistency, and reliability of data throughout its lifecycle.
Rationale: High-quality data is critical for informed decision-making and maintaining credibility.
Transparency and Accountability:
Principle: We commit to transparency in our data processes and hold ourselves accountable for data management.
Rationale: This approach builds trust and supports compliance.
Collaboration and Inclusivity:
Principle: We foster collaboration and ensure inclusivity in data-related decisions.
Rationale: This enhances effectiveness and incorporates diverse perspectives.
Data Domain Categorization
Data will be categorized as part of certain data domains based on type and origin in order to establish clear ownership within the organization. These domains are as follows:
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Framework diagram inspired by (Hopper, 2022)
Roles and Responsibilities
Inspired by (The complete guide to data governance roles and responsibilities, 2021)
Data Management Council
The Data Management Council is the group that brings together the appropriate individuals who fill the roles depicted in the framework above representing Applications, Research, the Data Steward, the Data Governance Lead, plus the Data Managers and Data Experts from the domain(s) whose data issue is being worked on by the group.
Executive Sponsor
Recommendation: Superintendent/President or VP of Administrative Services
The executive sponsor is a senior employee who is charged with coordinating responsible for data governance activities and programsprocess, actions, and outcomes. The role of the executive sponsor is to serve as the conduit between senior management and the data governance lead or Data Management Council and is authorized to make decisions and take actions.
(Recommendation for COS, Superintendent/President)
Data Governance Lead
The data governance lead is responsible for all aspects of defining and operating the data governance policies and supporting the multiple data domains. They are ultimately responsible for implementing the data governance program vision, promoting the role of governance and enforcing policy, while following data governance best practices.work with the Data Governance Lead to ensure that data governance is tied to the priorities of the district.
Data Governance Lead
Recommendation: Co-Lead between Dean of Research and Chief Technology Officer
Traditionally, this role sat under IT and tended to be the responsibility of the Chief Information Officer (CIO) or even the Chief Technology Officer (CTO). There are still quite a few organizations where this is still occurring, but it’s no longer recommended. In many institutions, this role sits with the head of the office of Institutional Research
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Tasked with defining and managing data governance policies across data domains. This role encompasses overseeing the implementation of the data governance program's vision, promoting governance practices, and ensuring policy adherence in line with best practices.
Regardless of the appointee(s), the primary function is to provide leadership, supportguidance, sponsorship, and understanding of data governance to other departments.
(Recommendation for COS, Co-Lead between Dean of Research and Chief Technology Officer)
and authoritative oversight in data governance matters across various departments.
Domain Owners
Domain Owners are members of Senior Management (Vice Presidents or direct reports to the Superintendent/President). These are individuals within the organization who are responsible for the overall management and governance of specific sets of data, referred to as "data domains." They are responsible for implementing the policies, standards and practices associated with the data in their domain area. As owners, they are also responsible for the appropriate treatment of data in their area ensuring quality, accuracy, completeness, security, and integrity of the data in their domain and should be aware of the regulations, policies, and laws governing data.
Domain Owners
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appoint Data Managers who are COS managers that will represent their domain within the data governance process. Depending on the size of the domain, multiple Data Managers may be needed to represent all data needs within the domain.
The Domain Owners will also ensure that the governance processes and decisions are followed within their domain, working with those they appointed within their normal reporting structures as Data Managers.
When data-related issues or conflicts arise, they take ownership of the issues and work with relevant teams to resolve and prevent similar issues in the future.
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Data
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Managers
Data Managers are COS managers who have been , appointed by their Domain Owner to represent the data within the domain area. These individuals should have decision making authority about business processes, definitions, data quality, data accessibility, and data retention requirements within their data domain. Data Managers need to know or be aware of the regulations, policies, and laws governing their data including data privacy laws. They also need to know the business needs, rules, procedures, and constraints associated with their data domain. Data Managers will be key members of the Data Management Council for their domain and should actively participate in creating data definitions, refining business practices, troubleshooting and resolving data related problems, and collaborating with other members of the Data Management Council to ensure the effective use and management of data across the districtDomain Owners, are responsible for their respective data domain(s). They have authority over business processes, data quality, access, and retention. Their role requires knowledge of relevant regulations, policies, and the specific business needs and constraints of their domain.
In the Data Management Council, Data Managers play a pivotal role. They actively contribute to defining data standards, refining business practices, solving data-related issues, and collaborating with council members for effective district-wide data management.
Data Managers have the authority to approve governance-related items finalized by the Data Management Council. For matters requiring higher-level approval, they are expected to promptly consult Senior Management and the Data Governance Lead.
Data Experts
Data Experts are the individuals within departments with extensive knowledge about key personnel in various departments who possess deep knowledge of specific data elements used in their daily work. Ideally, they know where the data lives, what it represents, how it is used, how it is entered and maintained. They are the front line for data quality management and work to identify and address data inconsistencies, errors, and missing data. They should assist in keeping documentation of business processes updated and will be brought into the Data Management Council as elements that relate to their data expertise are discussed or processed.
Constituents
constituents are any individual or group of individuals who have a vested . Their expertise encompasses understanding data location, significance, usage, entry, and maintenance. They play a crucial role in ensuring data quality by identifying and resolving inaccuracies and gaps. Additionally, they contribute to updating business process documentation and actively participate in the Data Management Council when matters related to their data expertise are addressed.
Constituents
Constituents are individuals or groups with a direct or indirect interest in specific data. They may be directly or indirectly affected by the collection, management, analysis, or usage of data within the organization. Data constituents can come from various departments and levels come from any department or level within the organization and may also play other roles within the data governance framework. A constituent brings issues into the data governance frameworkoften have dual roles, including bringing data-related issues to the attention of the Data Governance Council.
COS Data Steward
The COS Data Steward is a position within , part of the Technology Services Applications team at COS. In terms of data governance, this position serves to coordinate data governance processes for the district and oversees the maintenance of data definitions, data standards, best practices, training, and documentation of these items. The Data Steward will manage the workflow of items through the governance process, call meetings with Research and Applications to determine feasibility and priority of issues and call meetings bringing domain representatives into the Data Management Council to work through items that are within or affect their data domain. Lastly, coordinate the communication of items through the approval process by the Domain Owner(s), plays a central role in Sequoias CCD's data governance. This position is responsible for coordinating all data governance activities, maintaining data standards and definitions, and ensuring adherence to best practices. Key responsibilities include managing the governance workflow, organizing meetings with Research and Applications for issue assessment and involving domain representatives in the Data Management Council for relevant discussions.
Applications Representatives
Applications team representatives consist of The Applications Representatives on the Data Management Council comprise the Applications Manager and at least two others (other specialists, typically a Senior Programmer Analyst or and Programmer Analyst) to assist the group in the feasibility, priority, and collection of business specifications in order to complete the draft work. Depending on the Data Domain identified for the issue, the members from the Applications team that are most familiar will represent Applications on the Data Management Council. Their primary responsibilities are to evaluate the feasibility and priority of projects and to collect business specifications. The team members with the most relevant expertise will contribute to the Council for specific data domain issues.
Research Representatives
Institutional Research team representatives consist of one One or two members of from the Institutional Research office to assist the group in the feasibility, priority, and collection of business specifications in order to complete the draft work. They will also will serve as Research Representatives. Their primary responsibilities are to evaluate the feasibility and priority of projects and to collect business specifications. They will actively participate in the Data Management Council work.
Data Management Council
The Data Management Council is the group that brings together the appropriate individuals who fill the roles depicted in the framework above representing Applications, Research, the Data Steward, the Data Governance Lead, plus the Data Managers and Data Experts from the domain(s) whose data issue is being worked on by the group. The chart below depicts the workflow of an item through the governance process.
Path through the Data Governance Process's activities.
Data Governance Process and Swim Lanes
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Diagram inspired by (Ozturk, 2015)
1. Feasibility Assessment: Research and Applications staff assess each request to determine if it falls within the data governance scope and can be realistically implemented.
2. Prioritization: The Dean of Research and the Applications Director are responsible for prioritizing projects to align with district services and optimize resource utilization.
3. Business Specifications Completion: In cases of incomplete business specifications, the relevant staff and the originating constituents are responsible for collaborating to finalize these specifications on an as-needed basis.
References providing ideas and inspiration for the COS Data Governance model
Business Procedures Manual | 12.2 Governance Structure | University System of Georgia. (n.d.).
http://www.usg.edu. Retrieved December 6, 2023, from https://www.usg.edu/business_procedures_manual/section12/C2819
Data Governance Manual 2016 The Data Governance Manual outlines the purpose, structure, goals,
participants, and responsibilities of OSDE’s Data Governance Program. (n.d.). Retrieved December 6, 2023, from https://sde.ok.gov/sites/ok.gov.sde/files/Data Governance Program Manual 03112016.pdf
Data Governance. (n.d.). Arcadia University. Retrieved December 6, 2023, from
Data Governance Model. (2020, January 21). http://www.swarthmore.edu .
https://www.swarthmore.edu/data-governance/data-governance-model
Firican, G. (2021, December 20). Why data governance is a must for any organization. LightsOnData.
https://www.lightsondata.com/why-data-governance-is-a-must-for-any-organization/
Firican, G. (2023, May 17). The importance and benefits of data ownership in data governance. LightsOnData.
https://www.lightsondata.com/data-ownership-benefits-importance/
Hopper, A. M. (2022). Practitioner’s Guide To Operationalizing Data Governance. John Wiley & Sons.
Kimachia, K. (2022, September 8). An overview of data governance frameworks. TechRepublic.
https://www.techrepublic.com/article/data-governance-framework/
Meteyer, J. (2021, November 17). Data Governance - History, Present, and Future. Vimeo.
https://vimeo.com/647121328/8313d96fa5
Office of the Provost. (n.d.). Definitions: Data Governance and Data Domains - University of Rochester. Office
of the Provost. Retrieved December 6, 2023, from https://www.rochester.edu/provost/university-data/data-governance-overview/what-is-data-governance/
Ozturk, M. (2015). Partnership for Success: Geeks, Nerds and Techies Collaborate. College of the Sequoias.
https://www.cos.edu/en-us/Research/Documents/CAIR%20Geeks.pdf
The complete guide to data governance roles and responsibilities. (2021, November 22). LightsOnData.
https://www.lightsondata.com/the-complete-guide-to-data-governance-roles-and-responsibilities/
The Current State of Data Governance in Higher Education. (n.d.). http://Www.researchgate.net .
Welcome to Data Governance! - University of Maine System. (n.d.). Data Governance.
https://www.maine.edu/data-governance/
Who belongs on a high-performance data governance team? | TechTarget. (n.d.). Data Management.
Retrieved December 6, 2023, from https://www.techtarget.com/searchdatamanagement/feature/Who-belongs-on-a-high-performance-data-governance-team