Data Management Definitions
Enterprise Data Management – as defined by the data professional group DAMA, Data
Management is the development and execution of architectures, policies, practices and procedures
that properly manage the full data lifecycle needs of an enterprise. This also is the name of the ASMP
2.0 project area responsible for managing the program needs for data management.
Data Management Tool (DMT) – a software system that provides visibility into all the
details of reporting terminology and report specifications. Some examples of the type of
features within the DMT include clear, agreed upon definitions of institutional terms (business
definitions), a workflow for approving definitions and report specifications, tracking of business
process and technical documentation. See Institutional Metadata definition for additional
details. UT is currently evaluating DMT products with an eye toward using this as a way to
document data transitions throughout the ASMP 2.0 program.
Institutional Data Store (IDS) – the central data store to which data from operational
systems (“systems of record”) are stored for broad-based (read-only) retrieval by campus users.
The IDS will serve as the repository for all historical information that resides on the mainframe
(and possibly other data stores) where that data is not transitioned to Workday or any other
new system deployed as part of ASMP 2.0. The IDS will serve the primarily needs campus has
to (1) do cross-year reporting, (2) access historical information (3) access information where
data from more than one operational system is needed and (4) access data that does not have
the requirement to be real time (this use case is one way we intend to insulate campus units
from multiple transitions as our core HR, Payroll, Financial, Student and other systems change).
Data in the IDS are intended to be made available according to the proposed Data Access
Matrix developed by Data Stewards and the Data Management Committee (DMC). Given that
the IQ -Oracle database is well-established with efficient ETL and validation processes for a vast
amount of existing operational data, IQ will be leveraged in establishing the IDS (formerly called
the “master data repository”) for UT. Planning for the expansion of the IDS is currently
underway.
Data Management Committee - the primary governing body for Data Access Governance.
The DMC includes representatives from Data Trustees, Stewards, colleges and schools, and
executive administrative offices and under discussion is that its decisions and policy
recommendations through the Business Services Committee, the Operational IT Committee
and, ultimately, SITAB. The DMC is responsible for (a) refinements and addendums to Standards
and policies; (b) development of, and revisions to, Data Access Governance policies and
procedures; (c) development and adoption of Roles/Access rules; and (d) development and
management of mechanisms for access and use requests to be submitted to, and considered
by, the committee. The DMC may form workgroups or task forces as needed to inform policy
decisions or facilitate request/approval processes.
Data Governance – The overall governance of data quality, data management, data policies,
business process management visibility, and risk management surrounding the handling of data
in an organization. It has been proposed that responsibility for data access governance will
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reside with the Data Management Committee and its decisions and policy recommendations
will be submitted through the Business Services Committee, the Operational IT Committee and,
ultimately, to SITAB.
Data Continuity - the compatibility of past, present and future data in a way that allows
analysis and reporting independent of system changes, definitional changes or technology
platform differences.
Data Access - software and activities related to storing, retrieving, or acting on data housed
in a database or other repository.
Strategic Reporting – The type of reporting that answers questions addressing progress,
outcomes, and performance with respect to specific institutional goals or reports produced for
governing bodies.
Operational Reporting – The type of reporting that answers questions for operations and is
used by front line staff, managers, and processing units in order to facilitate institutional
operations and enable sound decisions to be made.
Institutional Data – any data element captured, extracted or derived from institutional
administrative information systems or residing in the Institutional Data Store (IDS) or an
associated central administrative data store. Specifically, data captured and stored by source
systems, or systems of record, or made available in the MDR or its affiliated databases.
Institutional information - a collection of institutional data which may be derived,
aggregated, calculated, or contained In any form, Including but not limited to documents,
memos, databases, spreadsheets, presentations, tables, charts, graphs, email and web sites.
Institutional Metadata – detailed information describing both the technical and business
characteristics of institutional data, including:
a. Definitions regarding the purpose, use and context of Institutional Data
b. Identification of which system is the official system of record of Institutional Data
c. Identification of personnel responsible for management of Institutional Data
d. Descriptions of how Institutional Data Is transferred, derived, and stored
e. Specific security and privacy practices that are used to safeguard Institutional Data
f. Risk and compliance classifications for Institutional Data
g. Rules concerning retention of records and Institutional Data
Source System or System of Record – the system by which any given institutional data
originate, are captured, or are initially processed is the “source system.” The “system of record”
is the authoritative system that defines and maintains a specific subset of institutional data (i.e.
the registration system is the system of record for student course enrollments). In most cases,
the System of Record is also the Source System. However, there are cases in which source
Data Management Definitions
system data are further aggregated or refined to produce official institutional information,
resulting in a separate authoritative System of Record for specific purposes (i.e. 12 th Class Day
data).
Departmental and Collateral Repositories – any of a number of departmental databases or
systems that process or present data to serve non-centralized administrative business needs;
these repositories may also redundantly store institutional data to support remote or
independent processes for use in specific units (i.e. not for official institutional or campus-wide
use).
Redundant Data Store – data that are available in the IDS but which are also stored on a
departmental or individual server, often for access by non-central administrative processes
which could likely be fed directly from the IDS. Redundant data stores refers to systematic or
large-scale repositories and not to individual spreadsheets or one-time ad hoc local databases
such as for the purpose of performing additional calculations, formatting, strategic analysis, or
transmittal.
Subject Area Domains - broad functional/operational areas for which major information
systems and databases are defined (i.e. “Research,” “Faculty,” “Fee Billing,” Financial Aid,”
“Admissions,” “Facilities,” etc.). Domains generally have one Data Steward (though there may
be several) representing the system(s) that form a given subject area.
Institutional Data Map – the formal reference document that associates each Subject Area
Domain with its Data Steward(s) and Trustee (i.e. business experts or “responsible parties”).
Data Access Matrix – the formal reference document that describes major data subject area
domains, the risk categories for specific data within each area, the roles of individuals to be
granted access to the data, and the level of granularity and scope of access for each role. The
Data Access Matrix is developed and maintained by the Data Steward for each subject area and
adopted and approved by the DMC.
External Entity – any person or organization not formally affiliated with UT Austin, including,
but not limited to: professional organizations, conference attendees, media, legislators or their
staff members, governing boards or administrative officials, other UT institutions, accreditors,
state or federal agencies, research associates from other institutions, or any member of the
general public (i.e. including public-facing web sites).
Non-Operational Use – access to, manipulation, or consumption of data for purposes other
than those which serve the common good of the university community or further its
effectiveness in achieving the institutional mission (such as those which facilitate administrative
processes or provide strategic insight for improved management of the institution). Examples
of non-operational use include individual faculty research projects, support for individual theses
or dissertations, or for uses that serve only the immediate needs of a single individual or unit
with no alignment with, or benefit to, institutional strategic initiatives.
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Associated Central Administrative Data Store – database or server that is populated by central
administrative systems or processes, or used for strategic institutional or reporting purposes,
but which contains data not held in the formal IQ/IDS. An example would be facilities data
maintained by Campus Planning and Facilities Services and held in the FAMIS database. There
is an implied link between this databases and the IQ/IDS, with the ability to access data across
servers.
Processing Unit – a central administrative office responsible for capturing and manipulating
data to facilitate operational processes, such as payroll, fee billing, registration, etc. Processing
units are usually managed by a Data Steward or Data Trustee and have Steward Analysts on
staff.
College Unit – offices reporting to a dean rather than central administration, but which may
engage in localized data processing or consumption in order to support operations within their
college or department. College units may have Application Developers on staff.
Data Trustees – VP and Associate VP administrators with portfolio level management
responsibilities over Subject Area Domain(s) and their System(s) of Record. Data Trustees are,
generally, members of the Business Services Committee; a subset of Data Trustees will provide
representation on the Data Management Committee. Data Trustees are ultimately responsible
for the appropriate availability and representation of institutional data that originate from their
Subject Area Domains or Systems of Record.
Data Stewards (custodians) – the operational managers for Subject Area Domain data and
Systems of Record. Data Stewards report to a Trustee, though, in some cases, the Steward may
also be the Trustee. Data Stewards and their staff have deep knowledge of the System(s) of
Record, definitions, processes, and business logic for their domain(s). Data Stewards assist with
metadata, modeling, risks assessments, roles/access recommendations, and validation. A
subset of Data Stewards will provide representation on the Data Management Committee.
IQ Steering Committee– the governing body that preceded the Data Management Committee
(DMC). This steering committee has been renamed the Data Management Committee and their
scope has been changed to accommodate the increased desire for institutional data access and
governance.
IQ Sponsors – the existing operational oversight group for IQ will continue in its current role
and also assume responsibility for implementation and coordination of the Data Access
Governance structure, maintaining a website with current policies and contact information,
facilitating DMC meetings and agendas, and communicating decisions and policies to campus
constituents.
Consumers –the end-user of central data, or the individual accessing and using the data for
consumption by a specific audience. Consumers are responsible for ensuring the security,
Data Management Definitions
appropriate use and dissemination of those data and, to the extent possible, the application of
appropriate definitions and methodologies in the presentation of those data, in accordance
with all existing UT data policies, including (but not limited to):
 Acceptable Use Policy
 Information Resources Use and Security Policy
 Data Classification Standard
 Data Encryption Guidelines
 Federal Education Rights and Privacy Act
IQ Team – the central IQ team provides technical expertise to maintain and enhance IQ and the
MDR and provide appropriate data quality, security, and availability on a consistent and timely
basis. The IQ team is responsible for establishing and maintaining Extract/Transformation/Load
(ETL) processes between steward area databases and the IDS, as well as the dimensional
modeling of data to meet business and definitional requirements established by the Data
Stewards and their analysts. IQ maintains the physical database as well as security schemas
and tools for appropriately accessing IDS data. IQ team members work with, and rely upon,
steward areas to establish and maintain the accuracy and integrity of steward area data, and to
appropriately reflect any changes in the source systems, on a continuous basis. In addition, the
IQ team is responsible for the implementation of appropriate backup and recovery strategies
for the MIDS.
Steward Analysts –personnel within a Steward’s business area who have deep expertise with
the systems and specific program logic by which data are captured and categorized, as well as
definitions, processing methodologies, and caveats associated with those data. Steward
analysts are familiar with data entity relationships, integrations with other steward areas, the
timing of data updates, and current or pending changes to the source systems. These
processing area analysts play a key role in the successful materialization of source system data
in the IQ/IDS and are vital to sustained data accuracy and availability. Steward analysts provide
expertise in source system tables, data definitions, joining data across tables, identifying and
documenting appropriate business logic, and validating data as it is materialized and modeled.
Further, steward analysts are responsible for ensuring that changes to source system data or
data structures are communicated to IQ team members so that consistent and appropriate
availability of data in the IDS can be maintained.
Application Developers – technical personnel who access data from the IDS and perform
additional, systematic manipulation of the data for presentation to a specific audience through
a programmed interface. Application Developers must ensure that all UT Acceptable Use and
Security policies (see above) are followed and that access to institutional data through their
systems is consistent with standards defined in the Data Access Matrix. Developers should
familiarize themselves with all available documentation on business rules, definitions, and
methodologies associated with the manipulation of institutional data and seek advice from
steward analysts, as needed, in order to maintain accuracy and consistent use of data
throughout the institution.