Frequently Asked Questions (FAQ)
Boston University Data Enablement helps the University understand, govern, access, document, share, and responsibly use institutional data.
This FAQ explains key Data Governance concepts, the broader Data Enablement approach, governance roles, access processes, analytics boundaries, and scope limitations.
About Data Governance and Data Enablement
What is Data Governance?
Data Governance is the framework of roles, responsibilities, standards, policies, norms, and processes used to manage institutional data throughout its lifecycle.
What is Data Enablement?
Data Enablement is the broader practice of helping authorized users find, understand, request, access, document, share, and responsibly use institutional data.
What is the difference between Data Governance and Data Enablement?
Data Governance establishes the framework for managing institutional data, including roles, responsibilities, standards, policies, accountability, and decision-making structures.
Data Enablement includes Data Governance while also supporting access pathways, metadata, documentation, communication, training, data literacy, responsible data sharing, and coordination across stakeholders.
In simple terms, Data Governance establishes the rules and norms. Data Enablement helps the University community understand, navigate, and apply those rules in practice.
Why did Boston University adopt the term Data Enablement?
Boston University adopted the term Data Enablement to reflect a broader mission than governance alone.
While Data Governance remains foundational, Data Enablement better describes the work of improving access, documentation, understanding, coordination, and responsible use of institutional data.
The rebrand reflects an evolution from a governance-only model toward a broader enablement model that balances appropriate oversight with usability, transparency, and access for authorized users.
Does the rebrand mean Data Governance is no longer important?
No. Data Governance remains a core part of Data Enablement.
Data Governance provides the structure, accountability, standards, and decision-making framework. Data Enablement builds on that foundation by helping people apply governance practices in practical, accessible, and consistent ways.
What does Data Enablement support?
Data Enablement supports data governance roles, access guidance, Data Use Agreement processes, metadata, data quality awareness, responsible data sharing, training, communication, and coordination across data stakeholders.
What Data Enablement Is Not
What is Data Enablement not?
Data Enablement does not replace Information Security, Legal, Compliance, Institutional Research, analytics teams, dashboard development teams, system administration teams, Data Warehouse administration, or departmental decision-making.
Is Data Enablement Information Security?
No. Data Enablement does not own cybersecurity, threat detection, vulnerability management, security operations, or incident response. Those responsibilities remain with the appropriate University security and technology teams.
Is Data Enablement Legal or Compliance?
No. Data Enablement may support governance processes and responsible data use, but it does not provide legal advice or official compliance determinations.
Does Data Enablement own institutional data?
No. Data Enablement does not own all institutional data. Accountability remains with designated University leaders, Data Trustees, Data Stewards, system owners, and business units.
Does Data Enablement approve all data access?
No. Data Enablement may coordinate or support access processes, but access approval depends on the data domain, system, sensitivity level, business purpose, and designated approvers.
Is Data Enablement the Data Warehouse administration team?
No. Data Enablement may support governance and access guidance related to institutional data platforms, but it does not operate, maintain, or administer the Data Warehouse.
Is Data Enablement responsible for source system data entry or corrections?
No. Data Enablement may help identify and communicate data quality issues, but source system data is maintained by the appropriate business units, system owners, and operational teams.
Does Data Enablement create institutional dashboards and analytics?
No. Data Enablement does not serve as the primary creator of all institutional dashboards, reports, analyses, or business intelligence products.
Data Enablement may partner with reporting, analytics, institutional research, and operational teams, but its primary role is to establish and support the governance framework that enables trusted, responsible, and consistent use of institutional data.
Data Enablement enables trusted analytics; it is not the sole producer of analytics.
What role does Data Enablement play in analytics and reporting?
Data Enablement works with business units, reporting teams, analytics teams, institutional research, and technical teams to promote shared definitions, governance standards, data quality practices, access rules, and responsible use of institutional data.
Data Enablement focuses on establishing the rules, standards, processes, and governance structures that help ensure reports, dashboards, and analyses are based on trusted and consistently understood data.
Is Data Enablement a replacement for departmental decision-making?
No. Data Enablement provides structure, guidance, and coordination. Departments remain responsible for their business processes, operational decisions, and appropriate use of data.
Institutional Data
What is institutional data?
Institutional data is information collected, created, maintained, or used by Boston University to support academic, administrative, research, operational, financial, student, employee, and institutional functions.
Why is institutional data important?
Institutional data supports University operations, planning, reporting, compliance, decision-making, student success, research administration, and institutional effectiveness.
Why is Data Governance important?
Data Governance helps ensure institutional data is accurate, secure, accessible to authorized users, consistently defined, and used responsibly.
Governance Roles
What is a Data Trustee?
A Data Trustee is a senior University leader accountable for a data domain. Data Trustees help establish strategic direction, accountability, and governance expectations for institutional data.
What is a Data Steward?
A Data Steward is responsible for the business oversight and responsible use of a specific data domain. Data Stewards help ensure institutional data is accurate, well-defined, appropriately accessed, and used responsibly.
What is a Data Custodian?
A Data Custodian is responsible for the technical management, protection, and operation of systems that store or process institutional data.
What is a Subject Matter Expert?
A Subject Matter Expert provides operational or business-process expertise about a data area and helps explain how data is created, used, interpreted, and maintained.
What is the difference between a Data Steward and a Data Custodian?
A Data Steward focuses on business oversight, meaning, appropriate use, and governance of data. A Data Custodian focuses on technical systems, infrastructure, security controls, and access implementation.
What is the difference between a Data Trustee and a Data Steward?
A Data Trustee is a senior leader accountable for a data domain. A Data Steward supports day-to-day business oversight and governance for that domain.
Data Access
How do I request access to institutional data?
A typical access process includes identifying the data needed, defining the business purpose, determining the system or source, completing required training, submitting an access request, obtaining approvals, and receiving access from the appropriate technical team.
Who approves access to institutional data?
Access may be approved by Data Stewards, Data Trustees, system owners, or other designated University approvers depending on the data, system, sensitivity, and intended use.
Can Data Enablement grant access directly?
No. Data Enablement may help coordinate or explain the process, but it does not independently grant access to all institutional data.
Why does access require approval?
Access approval helps ensure institutional data is used for appropriate business purposes, by authorized users, and in alignment with University policies, data sensitivity, and responsible use expectations.
Data Use Agreements
What is a Data Use Agreement?
A Data Use Agreement, or DUA, defines the terms and conditions for accessing, sharing, storing, protecting, and using data.
When is a Data Use Agreement needed?
A Data Use Agreement may be needed when data is shared, accessed, or used under specific conditions that require documented responsibilities, restrictions, protections, or approved purposes.
What does a Data Use Agreement clarify?
A Data Use Agreement may clarify what data may be used, who may use it, the approved purpose, storage expectations, sharing restrictions, retention expectations, and responsibilities of the parties involved.
Metadata and Data Quality
What is metadata?
Metadata is information that describes data, such as data definitions, field descriptions, business rules, source systems, data classifications, update frequency, and responsible parties.
Why is metadata important?
Metadata helps users understand what data means, where it comes from, how it should be interpreted, and who is responsible for it.
What is Data Quality?
Data Quality refers to the accuracy, completeness, consistency, timeliness, validity, and reliability of data.
Who is responsible for Data Quality?
Data Quality is a shared responsibility among business units, data creators, Data Stewards, Data Custodians, system owners, technical teams, and data users.
Responsible Data Use
What is responsible data use?
Responsible data use means accessing, sharing, analyzing, and applying institutional data only for approved purposes, with appropriate care for privacy, security, accuracy, context, and institutional policy.
Why do shared definitions matter?
Shared definitions help ensure that reports, dashboards, analyses, and decisions are based on consistent understanding of institutional data.
Why do rules and norms matter for data usage?
Rules and norms help create consistent expectations for how data should be accessed, interpreted, shared, protected, documented, and used across the University.