Data Governance Working Draft

Executive Summary

This document outlines the Data Governance 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.

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 be formed that would report to the President or designee and function as an “Operational Group” as defined in the Governance and Decision-Making Manual.

This group would be called the Data Management Council.

Guiding Principles

Inspired by (Hopper, 2022) and (Meteyer, 2021)

1. 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.

2. 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.

3. 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 based on type and origin to establish clear ownership within the organization:

The overall structure or framework for data governance is depicted in the following diagram:

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 responsible for data governance process, actions, and outcomes. The role of the executive sponsor is to 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.

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, guidance, 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 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.

Data Managers

Data Managers, appointed by Domain 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 key personnel in various departments who possess deep knowledge of specific data elements. 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 come from any department or level within the organization and often have dual roles, including bringing data-related issues to the attention of the Data Governance Council.

COS Data Steward

The COS Data Steward, part of the Technology Services Applications team, 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

The Applications Representatives on the Data Management Council comprise the Applications Manager and at least two other specialists, typically a Senior Programmer Analyst and Programmer Analyst. 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

One or two members from the Institutional Research office 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's activities.

Data Governance Process and Swim Lanes

Diagram inspired by (Ozturk, 2015)

References providing ideas and inspiration for the COS Data Governance model

Business Procedures Manual | 12.2 Governance Structure | University System of Georgia. (n.d.).

Data Governance Manual 2016 The Data Governance Manual outlines the purpose, structure, goals,

Data Governance. (n.d.). Arcadia University. Retrieved December 6, 2023, from

Data Governance Model. (2020, January 21). http://www.swarthmore.edu .

Firican, G. (2021, December 20). Why data governance is a must for any organization. LightsOnData.

Firican, G. (2023, May 17). The importance and benefits of data ownership in data governance. LightsOnData.

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.

Meteyer, J. (2021, November 17). Data Governance - History, Present, and Future. Vimeo.

Office of the Provost. (n.d.). Definitions: Data Governance and Data Domains - University of Rochester. Office

Ozturk, M. (2015). Partnership for Success: Geeks, Nerds and Techies Collaborate. College of the Sequoias.

The complete guide to data governance roles and responsibilities. (2021, November 22). LightsOnData.

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.

Who belongs on a high-performance data governance team? | TechTarget. (n.d.). Data Management.