Data Management for Higher Education

Creating a single student view

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Poor quality international data entering CRM systems across multiple different entry points, in multiple countries, in multiple languages, can create a significant data quality management problems for higher education establishments like universities, colleges, and schools.

Create a collaborative and easy to use Single Student View with Experian – overlaying data quality and data governance concurrently to enable an effective, automated data quality dashboarding system pre and post-migration.

De-risk your student data migration with Experian by:

  • Minimising the volume of historical data that requires brining across to the new system
  • Rapidly determining the amount of data cleansing that needs to take place to ensure the data is of sufficient quality which can then be loaded into the new system correctly
  • Quickly identifying the number of data quality issues that must be resolved and speeding up the effort required to fix poor quality data
  • Minimising the amount of data cleansing activities required after the migration
  • Assisting the simpler implemention of data retention policies
  • De-duplicating repetitive and redundant data by merging core data to create a single view of the student
  • Ensuring the data integrity is robust from the outset by establishing key relationships between core student entities
  • Providing self-documented and auditable transformation rules when converting legacy reference data to new target system data
  • Aiding with Data Governance strategies by ensuring data held is up to date, complete and accurate

 

Additional Benefits to Universities

As well as all of the risk mitigation advantages that Experian provides, dashboards can be built to quickly determine the demographic make-up of student information held. This is incredibly powerful when profiling applicant data and the preparation of Higher Education Students Early Statistics reports.

The University of Nottingham profiles 30 million rows across 5000 columns in 6 to 7 hours on a 4 core server. More cores would complete this work even faster.

The platform's ability to handle multiple languages such as Arabic, Russian, and Chinese data is invaluable for their multi-cultural university environment.

Post-migration day to day includes data cleansing, data quality dashboarding and quality rule validation across all the university’s data: student, staff, alumni, prospecting and more, from all sources.

Talk to our expert about arranging a Proof of Value today!