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Data Integrity: the Unisa Library experience 14-16 November 2011, North-west University (Potchefstroom Campus) Modiehi Rammutloa IR Quality Reporting Unisa.

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Presentation on theme: "Data Integrity: the Unisa Library experience 14-16 November 2011, North-west University (Potchefstroom Campus) Modiehi Rammutloa IR Quality Reporting Unisa."— Presentation transcript:

1 Data Integrity: the Unisa Library experience 14-16 November 2011, North-west University (Potchefstroom Campus) Modiehi Rammutloa IR Quality Reporting Unisa Library

2 What is the fuss about Data Integrity?

3 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

4 Aspects of data integrity

5 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)

6 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?

7 Data integrity unpacked Reliability - consistency of measurement. Same results repeatedly. Can your data be trusted? Can it be achieved? –Timely –Security –Completeness

8 Causes of bad data o Lack of data clean up o Migration of systems o Walk over technology o System generated (uploaded data from vendors) o Access rights - malicious modifications o Manual operations o Lack of standardization

9 Benefits of high quality data o Easy retrievability of information resources o Accessibility of the most relevant information o Customer satisfaction o Cost reduction (staff time saved) o Image of the Institution (e.g. High quality catalogue).

10 Data Governance structures o Millennium Working Group o Data Stewards (External Departments) o Data Integrity Steering Committees (Management Level)

11 Types of data at Unisa Patron dataProcurement Financial data Item & Bib data course reserve Unisa Library

12 Where do we get data from? o HR Oracle o Student system o Millennium o OCLC o 3 rd party information providers and publishers

13 Database - Application level Student system – 1.Applications 2.Registration 3.Study Material 4.Assignments 5.Examinations 6.Graduations Finance HR Uniflow - routing Library External databases Academic exam - XMO M y Un I s a AD E-mail University estates Hemis

14 Data correction flow accessaccess ICT’s domain Business domain 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, HR Examinations, assignments

15 Challenges o Importance of data integrity o Lack of training and ignorance o Commitment from data owners o 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 departments o Silos – databases all over the show

16 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

17 Into the future o Solid monitoring and evaluation processes o Identity management (University initiative) o Standardization of data o Validity checking system o Data Audit trails and controls o Data quality into Manager’s IPMS

18 Thank you! rammumw@unisa.ac.za (012) 429 2242


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