IT & MCIS

DEFINITION OF STANDARD: Enterprise data is that considered to be important to the administration, operations, or planning for a significant portion of or the entire institution. This data is typically stored, fed into or received from one of the official institutional databases maintained in a secure environment; is used as part of an official university report or to evaluate the attainment of strategic goals; or the existence and integrity of which must be guaranteed to comply with legal requirements and University needs. Data Administration and its advisory committees are responsible for developing standard names, definitions, formats, type, size and code values for enterprise data elements.

RATIONALE: Enterprise data is a critical institutional resource. As such, management of enterprise data must be approached in a comprehensive and systematic fashion. Regardless of the physical location of specific data within the organization, basic principles and guidelines of sound data management must be applied to ensure data integrity and integration, thereby maximizing the institutional investment. The University must develop a data infrastructure that provides high quality, timely and useful data that is easily accessible and understood by users, and meets the operational, management and strategic needs of the University. Enterprise data definitions and standards are a fundamental component of this data infrastructure. This information serves as a resource for data management, improves data quality, and provides sufficient information to enhance user understanding and analysis of data.

REVIEW CYCLE: Ongoing
RESPONSIBLE CONTACT:
Jayna Cheesman jayna@email.uky.edu

TIMELINE:
Revision date: June 5, 2003
Effective date: July 10, 2000

Recommended Standard(s):
Data Administration and its advisory committees are responsible for developing standard names, definitions, formats, type, size and code values for enterprise data elements. The Metatdata Database contains this information for over 5,000 data elements.

Technical Considerations:
Significant data redundancy and inconsistency currently exists within the IDMS systems, and among many sector and departmental systems. The institution has begun f evaluating the scope of this redundancy and its affects on data quality. Where possible, data in the source databases will be converted to the standard format and value ranges. Since some enterprise data elements are controlled by input from the Department of Education, the University is not free to update all data. In other instances, the cost to change existing institutional, sector or departmental systems may be too high; therefore, data correction will take place at the time of future conversion to a new system. In the interim, data loaded into the Data Warehouse for institutional reporting will be "cleansed" to adhere to enterprise data standards after its extraction from the source database and prior to its being loaded into the Data Warehouse.