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
o
o
o
o
o
o
Lack of data clean up
Migration of systems
Walk over technology
System generated (uploaded data from vendors)
Access rights - malicious modifications
Manual operations
Lack of standardization
Benefits of high quality data
o
o
o
o
o
Easy retrievability of information resources
Accessibility of the most relevant information
Customer satisfaction
Cost reduction (staff time saved)
Image of the Institution (e.g. High quality
catalogue).
Data Governance structures
o Millennium Working Group
o Data Stewards (External Departments)
o Data Integrity Steering Committees
(Management Level)
Types of data at Unisa
Patron data
Procurement
Unisa Library
Item & Bib data
course reserve
Financial
data
Where do we get data from?
o
o
o
o
o
HR Oracle
Student system
Millennium
OCLC
3rd party information providers and publishers
Database - Application level
Finance
M
y
Un
I
s
a
University estates
Student system –
1. Applications
2. Registration
3. Study Material
4. Assignments
5. Examinations
6. Graduations
HR
Hemis
Library
Uniflow - routing
Academic exam XMO
E-mail
AD
External
databases
Data and Information management model
Library
Business domain
systems
ICT’s domain
Data marts
Data
Data
a
c
c
e
s
s
Data
Data
Data
Data
Student, finance, HR
Examinations, assignments
users
Data correction flow
- Data cleansing projects
-Data integrity ID actions
- Data correction initiatives
- Report to DISC
Staging area
Challenges
o
o
o
o
o
o
o
o
o
Importance of data integrity
Lack of training and ignorance
Commitment from data owners
Data ownership (Branches - Patron)
Access rights (re-deployment of staff in different
sections)
No real time feedback (24 hours)
Data corrected on Millennium is overridden
Commitment from external departments
Silos – databases all over the show
What have we got in place?
o Headings report
o URL checker
o Database of non-compliances
- Inventory Team & Cataloguers
o ED Data Integrity Management Forum
o Data Stewards Forum
Into the future
o
o
o
o
o
o
Solid monitoring and evaluation processes
Identity management (University initiative)
Standardization of data
Validity checking system
Data Audit trails and controls
Data quality into Manager’s IPMS
Thank you!
rammumw@unisa.ac.za
(012) 429 2242