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Building Data Science Capabilities into University Data Warehouse to Predict Graduation

EasyChair Preprint no. 200

11 pagesDate: May 31, 2018


The discipline of data science emerged to combine statistical methods with computing. At Aalto University, Finland, we have taken first steps to bring educational data science as a part of daily operations of Management Information Services. This required changes in IT environment: we enhanced data warehouse infrastructure with a data science lab, where we can read predictive model training data from data warehouse database and use the created predictive models in database queries. We then conducted a data science pilot with an objective to predict students’ graduation probability and time-to-degree with student registry data. Further ethical and legal considerations are needed before using predictions in daily operations of the university.

Keyphrases: Business Intelligence, Data Warehouse, educational data science, GDPR, Graduation, institutional analytics, Predictive Analytics, time-to-degree

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Joonas Pesonen and Anna Fomkin and Lauri Jokipii},
  title = {Building Data Science Capabilities into University Data Warehouse to Predict Graduation},
  howpublished = {EasyChair Preprint no. 200},
  doi = {10.29007/57bl},
  year = {EasyChair, 2018}}
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