Data Integrity: the Unisa Library experience
14-16 November 2011, North-west University (Potchefstroom Campus)
Modiehi Rammutloa
IR Quality Reporting
Unisa Library
What is the fuss about Data Integrity?
What is data integrity
Data integrity implies that the data system, the process and the content of the data are reliable, consistent and accurate
Sen-Yoni Musingo (2008)
Data Integrity is essential in order for data to be considered credible
Data quality is a perception or an assessment of data’s fitness to serve its intended purpose in a given context.
www.searchdatamanagement.techtarget.com
Aspects of data integrity
Data integrity unpacked
o Accuracy - Closeness of measurement to the expected value.
Accuracy can be achieved if data is clean and precise– mechanisms to detect & correct (EDCS)– Business rules (eliminate duplication)– 24/7 approach in data maintenance??– Checks and balances– Default values (using 0 – no empty field)
Data integrity unpacked
o Consistency - Data as it is at any given point
How is that achieved?
- Standardization (agreement on processes)
- Automation of processes (Special membership)
- Back up systems?
Data integrity unpacked
Reliability - consistency of measurement.
Same results repeatedly. Can your data be trusted?
Can it be achieved?– Timely– Security– Completeness
Causes of bad data
o Lack of data clean upo Migration of systemso Walk over technologyo System generated (uploaded data from vendors)o Access rights - malicious modificationso Manual operationso Lack of standardization
Benefits of high quality data
o Easy retrievability of information resourceso Accessibility of the most relevant informationo Customer satisfactiono Cost reduction (staff time saved)o Image of the Institution (e.g. High quality
catalogue).
Data Governance structures
o Millennium Working Groupo Data Stewards (External Departments)o Data Integrity Steering Committees
(Management Level)
Types of data at Unisa
Patron data Procurement
Financial
data
Item & Bib data
course reserve
Unisa Library
Where do we get data from?
o HR Oracleo Student systemo Millenniumo OCLCo 3rd party information providers and publishers
Database - Application level
Student system –1.Applications2.Registration3.Study Material4.Assignments5.Examinations6.Graduations
Finance
HR
Uniflow - routing
LibraryExternal databases
Academic exam - XMO
My UnIsa
AD
University estates
Hemis
Data
Data correction flow
Data
Data
Data
access
ICT’s domainBusiness domain
Data
Data
Data marts
Staging area
Library
users
systems
Data and Information management model
- Data cleansing projects-Data integrity ID actions- Data correction initiatives- Report to DISC
Student, finance, HRExaminations, assignments
Challenges
o Importance of data integrityo Lack of training and ignoranceo Commitment from data ownerso Data ownership (Branches - Patron)o Access rights (re-deployment of staff in different
sections)o No real time feedback (24 hours)o Data corrected on Millennium is overridden o Commitment from external departmentso Silos – databases all over the show
What have we got in place?
o Headings reporto URL checkero Database of non-compliances
- Inventory Team & Cataloguerso ED Data Integrity Management Forumo Data Stewards Forum
Into the future
o Solid monitoring and evaluation processeso Identity management (University initiative)o Standardization of data o Validity checking systemo Data Audit trails and controlso Data quality into Manager’s IPMS