Data governance is the formalizing of a process focused on managing the quality, consistency, usability, security, and availability of information. It is a decision-making and cross-functional charter established to create data management policies, processes, and standards to optimize the institution’s return on its data assets. This policy outlines a multi-pronged approach addressing the definition, production and usage of data to manage risk and improve the quality and usability of the data.
I.Data Change Control / Data Stewardship
Successful data governance requires the participation and collaboration of functional experts and stakeholders who will inform and guide the processes. The participants will act in several connected roles all related to data creation, protection, and recording.
Membership shall consist of representation from the following organizational units:
- Office of Admissions and Recruitment
- Advancement/Alumni Affairs
- Office of Enrollment Management Reporting and Operational Intelligence
- Office of the Registrar
- Office of Financial Aid
- Graduate School
- Office of Global Engagement
- Office of Institutional Research
- Enterprise Application Services
- IS Security
- Business Services
- Human Resources
Detailed descriptions of proposed functions/activities of this group follow.
IA.Change Control Board (CCB)
To review and approve changes that will impact the landscape of student systems and applications. The CCB will act as the official review body of functional configuration and technical code changes relative to campus-level information systems at Purdue University Northwest, and make recommendations to the decision-makers.
To have constant alignment between business processes, technical requirements and reporting for the purpose of common, consistent and reliable information usage, language and meaning among information consumers.
- The CCB website will have an intake form for proposed changes.
- The CCB facilitator will maintain a log of requests and forward them to the CCB members to initiate the review and approval process.
- The review process begins with a consideration of stakeholder impact which may necessitate review and or feedback from identified stakeholders.
- The criterion for approval will be determined by the convening Change Control Board and may vary by proposed change (based on impact, complexity, etc.)
IB. Data Stewardship
To oversee establishment of data management policies, procedures, and accountability for data governed within their collection. The data stewards will help create and actively participate in processes that would allow the establishment of business-context-defined, data quality goals and be accountable for improving the data quality of the information domain they oversee.
A data stewardship program identifies, defines and protects data across the institution. An active stewardship program allows the institution to improve the understanding of data assets, discover the relationships among the data, consolidate metadata (data describing the data) and ultimately support the transformation of data into actionable information.
Tasks and responsibilities assigned to data steward include the following:
- Become familiar with University Data Policies and work with Information Services to establish security/access guidelines for data.
- Assure that data is classified as restricted, sensitive or public as it relates to the distribution of the data. Identify procedures for maintaining data confidentiality as they relate to data under the Data Steward’s management. When necessary, work with departmental Security Officers to enforce the procedures.
- Assure that there are documented and published processes for granting system access and privileges in the business area.
- In accordance with established guidelines, grant or remove access by role or by person.
- Provide and track appropriate certification or training prior to granting access to the requested data or system. Training may include but is not limited to the Purdue University Data Handling, FERPA, GLBA and Data Confidentiality Guidelines.
- Develop operational procedures and processes to ensure that data is entered and stored accurately.
- Review and approve individual requests for data and the use of requested data. As needed, obtain a signed Memorandum of Understanding from the head of organizational units requesting the ability to extract or use data from a system under the Data Steward’s management.
- Establish and maintain an appropriate structure and review process for responsible management of file shares.
- As needed, participate in the management of shared data in ERP systems supporting the Data Steward’s business area. Annually review and maintain updates to data standards manuals relevant to the Data Steward’s business area.
- Resolve discrepancies across business units and systems – this is a continuing process.
Data stewards’ responsibilities can be grouped into four main areas: operational oversight; data quality; privacy, security, and risk management; and policies and procedures. These front-line subject matter experts can most effectively convey the relationship between data and the business processes, decisions and interaction most relevant to the institution. They ensure compliance with defined data governance guidelines to deliver trusted, secure data.
- Data stewards provide university-level knowledge and understanding for a specific data area (e.g., student data, financial data, HR data, or alumni data) including how data in their portfolio are collected, maintained, and interpreted.
- Data stewards are responsible for promoting appropriate data use through planning, policy, and protocols.
- Data stewards are responsible for data quality and data integrity, including consistent data definitions and their application throughout connected systems. They collaborate with other stewards to ensure that overlap areas (e.g., student employees and employees who are students) work across the board.
- Data stewards work with security, privacy, and compliance officers to ensure that data are classified appropriately and that training is provided to users who will interact with data.
- Data stewards will help to develop data metrics to measure accuracy, compliance, completeness, consistency, utility, efficiency, and user satisfaction.
IC. Data Dictionary Creation/Maintenance
To create and maintain central and authoritative set of data definitions to facilitate clarity in reporting and discussions.
As the institution continuously collect and analyze ever increasing amounts of data, valuable information is wasted because people don’t describe or understand data in the same way across the organization. Formal and centralized documentation of campus information is key to the constant alignment between business processes, technical requirements and reporting for the purpose of common, consistent and reliable information usage, language and meaning among information consumers.
- Data Item / Label / Field / Name
- Definition Functional / Technical
- Related report examples
- Changes / Change History (Who, What, When, Where, Why, How)
- Team with campus wide representation will define, align and refine business terminology.
- Minimal ad hoc submissions with an annual review of the full dictionary
II.Data Cookbook (Software Solution to Facilitate Data Governance)
With the focus on data governance, there is a need for metadata software to facilitate an enterprise source of data definitions, metadata, and lineage along with workflow, search capabilities and collaboration tools. This is a key component of a data governance strategy.
With the ongoing need to utilize data for decision-making, data is an institutional asset. With the enterprise systems in place, as well as numerous other local and system wide data sources, the ability to access, understand, connect and effectively use one of our key resources, DATA, is complex. Currently data ownership, metadata management is piecemeal or lacking. The Data Cookbook software would:
- Improve accurate use of this asset,
- Highlight the need and ways to improve data quality,
- Support best practices in data management, and
- Enable standard processes that establish a clear path from question to answer. For example:
- Standard process for searching for a report. Allows search, if need a new report, there is a process for requesting it; for author to gather requirements, vet, approve, and produce report. Re-use of definitions. Saves time, increases consistency and establish common language.
- New report requests can lead to refinement of data which is continuous quality improvement.
- Process ties together requesters, authors, operational sources of data, reporting oversight
- Data Dictionary: Casual consumers can search for functional (English) definitions but others can view the technical definitions (data system source, SQL statements, join info, caveats, etc.)
- Report library and integrated content from external entities that are sources of definition (IPEDS, Common Data Set, National Student Clearinghouse, other higher education institutions, etc.)
- Links into reporting tools including Cognos, Tableau and SAP
- Searchable report specifications allow users to see if existing report will meet their needs. It includes the business purpose, data items, definitions, caveats, report location and author.
- Workflow allows implementation of a RACI (Responsible, Accountable, Consulted, and Informed) model of responsibility
- Collaboration Tab allow users of various roles (requester, business analyst/developer, data steward, queue manager, data consumer) to communicate and share relevant information and address tasks related to various aspect of data governance.
- Task list of items assigned and information requests
- Consumer can comment and ask questions to which the moderator can post a response.
- Changes to data definitions can be communicated out or individuals can watch a discussion.
- Full implementation by iData in collaboration with the institution
- Update of data dictionary
- Documentation of business process changes
- Upkeep of report library
III.Related External Topics
Data Entry Standards
Accurate data is crucial to Purdue University Northwest. The standardization of all data entered into its enterprise systems are essential to maintain data integrity. Data entry standards must be followed very closely by all who enter information into the enterprise systems to ensure data integrity. The purpose of the data entry standards manual is to convey Purdue University Northwest’s data standards and its employees’ responsibilities regarding those standards.
The members of the Data Standards Committee are responsible for developing the data standards, maintaining the data entry standards manual, and to facilitate university training on data entry. The committee must approve any changes recommended for the data standards in use and communicate these changes to all stakeholders. The most current version of the manual will be made accessible to all employees that enter or report on data in enterprise systems.
Data security means protecting data, such as a database, from destructive forces and from the unwanted actions of unauthorized users. Information technology policies are under the purview of Information Services and the safeguard of data asset is the responsibility of all employees. The goal of these policies are to assure employees access to relevant data they need to conduct University business, prevent unauthorized access to systems, data, facilities, and networks and prevent any misuse of, or damage to, computer assets or data.
Data-Informed Academic Enrollment Management
Academic administrators need accurate data to monitor enrollments, identify trends, and implement new curricula which meet current and emerging student needs. Those who fill College and Departmental leadership roles are charged with recruiting students, creating programs that address current student interests and needs, and maximizing enrollments. Data and reports provided by Institutional Research will aid the Colleges / programs in fulfilling this charge.
This is a living document and will be revised as the situations and needs warrant.
Initial version: December 19, 2016
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