Details

University Data Quality Initiative

Implementation of data quality initiatives with the aim to improve the university’s data quality and to ensure smooth data governance of the university.

SCOPE
  • Implementing data quality initiatives in phases according to students, staff, facilities, research and publications data domain.
  • Establishing a Standing Committee that is responsible for the university data quality management.
  • Creating a platform to automate the management of university data quality. 
 
OUTPUT
 
  1. Framework on University’s Data Quality Management.
  2. Data quality management platform.
  3. Committee or team that manages university data quality.
  4. University data quality status reports that contain findings related to issues of university data quality.

IDENTIFIED DATA QUALITY ISSUES
  1. Incomplete data (blank) - Data for certain fields in a record are incomplete for a particular data format required by MoHE (MyMoheS).
  2. Lack data format uniformity for a field – Possibilities exist where the input data format for certain fields of data type (data type) are not the same, such as text, number, date and etc.
  3. Relation of data between formats - Detailed data do not have the master record (for example RD1: Research Data (Master Data) and RD1-1: Internal Researcher Data).
  4. Redundant data - Duplication of the same record exists in a particular data set.
  5. Inaccurate mapping between UiTM and MoHE codes. There exist university codes that do not map against the MoHE’s codes in the MyMoheS.
 

CHALLENGES
  1. Data volume (size) and scope (large)
  2. MoHE’s data requirements by that cannot be automated and must be dealt with manually.
  3. Automation of information management through a system that is managed by respective centre of responsibility.
  4. Poor control of data entry that contributes to inferior data quality

ACTIVITIES THAT HAVE BEEN CARRIED OUT

Perhaps to arrange the above by specific activities (meetings, workshops, audit, etc)

  • Meeting:
  1. Project data quality: April 28, 2014, May 15, 2014, and March 23, 2015
  2. Issues on Students Data Quality (Enrolment) Session 1 2014/2015: March 31, 2015, April 22, 2015 and November 2, 2015.
  3. MyMoheS-MyRA Integration: April 14, 2016
  4. University Data Management: May20, 2016
  5. Student Data Quality Module: October 6, 2016
  6. Staff Data Quality Module: October 13, 2016
  • Workshop/training:
  1. Data quality software training using SAS Data Flux Data Management Studio Basic: 28-30 April 2014.
  2. Research, Consultancy and Publications Data Quality: May 4, 2016 at Lab 1, Infostructure Department, level 5, Menara Sultan Abdul Aziz Shah (SAAS).
  3. Participation in Exhibition, Intellectual Property and Commercialization Data Quality: May 12, 2016 at Research Innovation Business Unit (RIBU).
  • Audit

MyMoheS Data Quality: August 29, 2016 by MOHE at UPMO, Level 1, UiTM Chancellery Building

 

 

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