Data Governance Working Group @ Columbia University
A central place for all Data Governance related activities and Information.
Data Governance at Columbia University
The Data Governance at Columbia University is guided by the Data Governance Working Group (DGWG). DGWG plays a crucial role in overseeing the use, management, and governance of data across the institution. Its primary objectives include:
- Developing a comprehensive data governance framework and oversight.
- Providing guidelines on data security and compliance.
- Promoting data quality, integrity, and availability.
- Promoting data literacy.
- Managing the entire data lifecycle effectively.
The Working Group continuously assesses data needs and implements control measures throughout the data lifecycle. This ensures stakeholders have secure access to reliable and timely data and analytics.
Key responsibilities of the Data Governance Working Group include:
- Provide guidance in establishing and maintaining policies and procedures to monitor and ensure data quality, integrity, confidentiality, and security.
- Aligning with the university’s data strategy and data privacy policies.
- Promoting compliance with governmental laws and regulations.
Through these efforts, the Data Governance Working Group aims to foster a data-driven culture that supports informed decision-making and strategic planning at Columbia University.
The primary drivers for this working group are:
- Continuously evaluate needs for data governance, and data life cycle management as the technology and business needs evolve.
- To avoid data silos and improve data integrity at enterprise level.
- Understand the data lineage and improve data access and integration framework.
- Form common vocabulary, data literacy and metadata. management framework across the university
- Improve data quality.
- Provide a centralized framework for Information life cycle management.
- Promote data governance across the enterprise.
- Promote data governance and data security and compliance adherence at the enterprise level.
- Evaluate and standardize tools and business processes in support of information lifecycle management.
The DGWG will have an oversight of all the data and information that is created, maintained, stored and archived across the university except research and medical data. To further clarify the main scope of this working group is all the data and information that is associated with administrative use of the university’s day to day operations.
A detailed list of all the systems under DGWG’s oversight is listed below.
Note: The scope of DGWG does not cover research data.
- Data Lifecycle management: provide a definitive guidance and framework for data lifecycle management across Columbia University.
- Data Policies and Frameworks: Data governance involves the ongoing review, development and implementation of data policies, frameworks, and guidelines that govern how data is managed, protected, and used across the organization. This includes policies related to data quality, data privacy, data security, data sharing, and compliance with regulatory requirements.
- Data Architecture and Management: Data governance addresses the design and management of data architecture, including data models, data structures, and data repositories. It defines standards and best practices for data integration, data storage, data access, and data lifecycle management.
- Data Stewardship and Ownership: Data governance assigns data stewards or data custodians responsible for specific data domains, ensuring accountability and ownership of data quality, data integrity, and data compliance. Data stewards work in collaboration with business units to manage and govern data effectively.
- Data Quality Management: Data governance includes processes and controls to monitor, measure, and improve data quality. It establishes data quality metrics, data profiling techniques, and data cleansing procedures to ensure that data is accurate, complete, consistent, and reliable.
- Data Security and Privacy: Data governance addresses data security and privacy concerns by defining policies and practices to safeguard sensitive and confidential information. It educates and promotes compliance with data protection regulations, establishes access controls, encryption measures, and monitors data usage to prevent unauthorized access or data breaches.
- Data Compliance and Regulatory Requirements: Data governance ensures that the organization adheres to relevant data regulations, industry standards, and compliance requirements. It establishes mechanisms for data auditing, data classification, data retention, and data governance reporting to demonstrate compliance and mitigate risks.
- Data Governance Roles and Responsibilities: Data governance defines roles and responsibilities within the organization for data management, data stewardship, and data governance activities. It clarifies the responsibilities of data owners, data custodians, data stewards, and data users, promoting a clear accountability structure.
- Data Integration and Interoperability: Data governance addresses the integration and interoperability of data across systems, applications, and business units. It establishes data standards, data formats, and data exchange protocols to ensure data consistency and compatibility.
- Data Culture and Training: Data governance promotes a data-driven culture within the organization by fostering data literacy, awareness, and skills. It provides training and education programs to enhance data management practices, data governance understanding, and data-related decision-making capabilities.
- Data Governance Metrics and Monitoring: Data governance establishes metrics and performance indicators to monitor the effectiveness of data governance initiatives. It measures data quality, compliance, and the adherence to data governance policies, enabling continuous improvement and proactive management of data assets.
The scope of data governance may vary across organizations based on their size, industry, and specific data requirements. However, it generally encompasses the areas mentioned above to ensure comprehensive management, protection, and utilization of data assets throughout the organization.
Data Governance Working group Charter:
https://docs.google.com/document/d/15GfE855ZGVn-JU8TqaaUzFkmgdriBKjYaiQrBx8sGqs/edit?usp=sharing
The Data Governance Working Group is initiated by the IT Leadership Council to ensure
appropriate mechanisms are in place to develop a culture and an operational framework that
recognizes data as an asset of the University, and leverages its use to promote data driven
decision making across the institute. This framework will also ensure data quality, integrity, and
accessibility that complies with university security policies and standards.
The ITLC has vested the authority in this committee to develop data governance standards, evaluate and recommend changes to the policy and procedure to carry out the responsibilities listed below:
- Continuously evaluate and define scope of University data asset managed and governed by the DGWG
- Develop enterprise information management standards and framework for the university
- Operational Oversight, Data Access, Data Transport, Data Retention, and Archiving
- Privacy, Security, and Risk Management
- Share and educate decision makers and staff across the University
Membership:
The DGWG membership consists of representation from Provost, Institutional Research, CUIT, CUIMC, OGC, Schools, Registrar’s office, HRIS and Data Stewards. It is required that DGWG members attend the meetings regularly and participate in completing assigned tasks.
It is expected that members participate in the meetings regularly and actively participate in meetings and activities.
Failure to actively participate in these activities may result in termination of the membership.