Electronic Records Management at Tulsa Community College

The Role of Data Stewards

Data stewards are the linchpin of effective data governance. They are individuals responsible for overseeing the quality, integrity, and security of specific data domains within TCC. Their role is critical in ensuring that data is aligned with business objectives and meets regulatory requirements.

Key Responsibilities of Data Stewards at Tulsa Community College

1. Data Quality Ownership:
   • Ensuring data accuracy, completeness, consistency, and timeliness.
   • Developing and implementing data quality standards and procedures.
   • Monitoring data quality metrics and taking corrective actions.
2. Data Access and Usage:
   • Submitting, reviewing and approving data access requests through ProcessMaker request forms.
   • Monitoring data usage to identify potential misuse or unauthorized access.
3. Data Lifecycle Management:
   • Overseeing data creation, storage, retrieval, and disposal.
   • Ensuring adherence to data retention and disposition policies.
4. Data Governance Policy Enforcement:
   • Educating department stakeholders on data governance policies and procedures.
   • Identifying and addressing non-compliance issues.
   • Promoting a culture of data stewardship within their departments.
5. Data Privacy and Security:
   • Ensuring compliance with data privacy regulations (e.g., FERPA, HIPAA).
   • Implementing data security measures to protect sensitive information.
   • Responding to data breaches and security incidents.

Selection and Training of Data Stewards

• Criteria for Selection: Data stewards should have a deep understanding of their respective department data domains, strong analytical skills, and a commitment to data quality.
• Training and Development: Provide data stewards with training on data governance principles, data quality techniques, data security best practices, and relevant regulations.

Challenges and Best Practices

• Overburdened Stewards: Ensure that data stewards have adequate resources and support to fulfill their responsibilities.
• Lack of Data Literacy: Provide training and resources to improve data literacy among stakeholders.
• Data Silos: Encourage collaboration and data sharing across departments to break down data silos.
• Technology Limitations: Invest in tools and technologies to support data stewardship activities.

By empowering data stewards and providing them with the necessary resources, Tulsa Community College can establish a strong foundation for data governance and ensure the effective management of its valuable data assets.

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Understanding the Importance

A well-defined data retention and disposition policy is crucial for several reasons:

• Legal Compliance: Ensuring adherence to regulatory requirements such as FERPA, HIPAA, and GDPR.
• Risk Mitigation: Reducing the risk of data breaches and unauthorized access.
• Storage Optimization: Identifying and eliminating unnecessary data to optimize storage costs.
• Operational Efficiency: Streamlining data management processes.

Key Components of the Policy

1. Retention Schedules:
   • Classification: Categorize data based on sensitivity, legal requirements, and business value (e.g., critical, sensitive, general).
   • Retention Periods: Determine appropriate retention periods for each data category, considering factors like legal mandates, business needs, and data age.
   • Review Frequency: Establish a schedule for reviewing and updating retention schedules to align with changing regulations and business requirements.
2. Disposal Procedures:
   • Secure Destruction: Implement secure methods for destroying data, such as shredding, degaussing, or data overwriting.
   • Certification: Require certification from authorized personnel to confirm that data has been disposed of securely.
   • Documentation: Maintain records of data disposal activities for audit purposes.
3. Data Archiving:
   • Criteria: Define criteria for archiving data, such as age, legal requirements, or business value.
   • Storage Methods: Determine appropriate storage methods for archived data, such as cloud storage or physical media.
   • Access Controls: Implement robust access controls for archived data to prevent unauthorized access.
4. Data Deletion:
   • Criteria: Establish criteria for deleting data, such as when it reaches its end-of-life or is no longer required for business operations.
   • Deletion Procedures: Implement secure procedures for deleting data, including overwriting or physically destroying storage media.

Tailoring the Policy to Tulsa Community College

• FERPA Compliance: Ensure strict adherence to FERPA guidelines, which mandate the retention of student records for a specific period.
• Academic Records: Develop specific retention schedules for academic records, including transcripts, test scores, and course materials.
• Financial Records: Establish retention periods for financial records, such as tuition payments, grants, and scholarships.
• Research Data: Determine retention requirements for research data, considering factors like grant agreements and publication timelines.
• Employee Records: Define retention periods for employee records, including personnel files, performance reviews, and payroll information.

By developing a comprehensive data retention and disposition policy, Tulsa Community College can ensure compliance with regulations, reduce risks, and optimize data management processes.

Data Analytics and Reporting is a critical component of the data governance framework for Tulsa Community College (TCC). It enables the institution to extract valuable insights from its data, make informed decisions, and improve operational efficiency.

Key Components and Considerations:

1. Data Warehouse or Data Lake:

• Purpose: A centralized repository for storing structured and unstructured data from various sources within TCC.
• Considerations:
  • Scalability: The chosen solution should be able to handle increasing volumes of data.
  • Performance: Ensure efficient data retrieval and analysis.
  • Integration: The data warehouse or data lake should seamlessly integrate with existing systems and data sources.

2. Data Visualization Tools:

• Purpose: Tools used to create interactive and visually appealing reports and dashboards.
• Considerations:
  • Ease of Use: The tools should be user-friendly, even for non-technical users.
  • Customization: Allow for customization of reports and dashboards to meet specific needs.
  • Integration: Integrate with the data warehouse or data lake to access and visualize data.

3. Data Analytics Techniques:

• Descriptive Analytics: Summarizing and describing existing data.
• Diagnostic Analytics: Identifying the root causes of problems or trends.
• Predictive Analytics: Forecasting future outcomes based on historical data.
• Prescriptive Analytics: Recommending optimal actions based on data analysis.

4. Business Intelligence (BI) Tools:

• Purpose: Software applications that provide a comprehensive view of business data.
• Considerations:
  • Functionality: BI tools should offer a wide range of features, including reporting, analysis, and data mining.
  • Scalability: Ensure the BI tool can handle the growing data needs of TCC.
  • Integration: Integrate with the data warehouse, data lake, and other systems.

5. Data Governance for Analytics:

• Data Quality: Ensure the data used for analytics is accurate, complete, and consistent.
• Data Security: Implement appropriate security measures to protect sensitive data.
• Metadata Management: Maintain accurate metadata to describe data elements and relationships.
• Data Access: Establish clear guidelines for data access and usage to prevent unauthorized access.

6. Use Cases for Data Analytics:

• Student Success: Analyze student performance data to identify at-risk students and provide targeted support.
• Financial Management: Track financial performance, identify cost-saving opportunities, and optimize resource allocation.
• Operational Efficiency: Analyze operational data to identify inefficiencies and improve processes.
• Fundraising: Analyze donor data to identify potential donors and optimize fundraising efforts.

By leveraging data analytics and reporting, TCC can gain valuable insights into its operations, make data-driven decisions, and improve outcomes for students, faculty, and staff.

Data Security and Privacy is a cornerstone of any effective data governance framework. It ensures that sensitive information is protected from unauthorized access, disclosure, alteration, or destruction.

Key Considerations for TCC

1. Data Classification:
   • Sensitivity Levels: Categorize data based on its potential impact if compromised. For example, TCC might classify data into categories such as "Highly Confidential" (e.g., student financial records, medical information), "Confidential" (e.g., academic transcripts), and "Public" (e.g., general campus announcements).
   • Regular Review: Conduct periodic reviews to ensure that classification levels remain accurate and relevant.
2. Access Controls:
   • Role-Based Access Control (RBAC): Assign access privileges based on an individual's role or function within TCC. For instance, a faculty member might have access to student grades and attendance records, while a registrar would have broader access to student data.
   • Least Privilege Principle: Grant users only the minimum level of access necessary to perform their job duties.
   • Multi-Factor Authentication (MFA): Require users to provide multiple forms of identification (e.g., password, biometric data, security token) to access sensitive systems.
3. Incident Response Plan:
   • Incident Identification: Establish procedures for detecting and reporting data breaches or security incidents.
   • Containment: Quickly isolate compromised systems to prevent further damage.
   • Investigation: Conduct a thorough investigation to determine the cause and extent of the incident.
   • Eradication: Remove the root cause of the incident.
   • Recovery: Restore systems and data to a secure state.
   • Lessons Learned: Analyze the incident to identify areas for improvement and prevent future occurrences.
4. Employee Training and Awareness:
   • Security Awareness Programs: Educate employees about data security best practices, including password management, phishing prevention, and recognizing signs of social engineering attacks.
   • Regular Training: Conduct periodic training sessions to reinforce security awareness and address emerging threats.
5. Compliance with Regulations:
   • FERPA: Ensure compliance with the Family Educational Rights and Privacy Act, which protects the privacy of student records.
   • HIPAA: If applicable, comply with the Health Insurance Portability and Accountability Act, which governs the privacy and security of health information.
   • Other Regulations: Be aware of and comply with any other relevant state or federal regulations.
6. Third-Party Risk Management:
   • Vendor Assessments: Evaluate the security practices of third-party vendors who have access to TCC's data.
   • Contracts: Include strong data security clauses in contracts with vendors.

By implementing these measures, TCC can significantly enhance its data security posture and protect sensitive information from unauthorized access and misuse.