Professor Aspen Olmsted and master’s student, Gayathri Santhanakrishnan, were selected as “Best Paper” for “Cloud Data Denormalization of Anonymous Transactions.” Selection was based on reviews of the original submission, camera-ready version, and presentation during the 2016 Cloud Computing Conference in Rome, Italy.
In the paper, Dr. Olmsted and Santhanakrishnan investigated the problem of representing transaction data in PAAS cloud-based systems. They compared traditional database normalization techniques with our denormalized approach. In the research, they specifically focused on transactional data that is not attached to a specific customer. The absence of the relationship in the customer object allowed for the vertical merging of tuples to be stored in aggregate form. The journaling featured the data store, allowing full audits of transactions while not requiring anonymous data to be materialized in fine-grained levels. The horizontal merging of objects is also deployed to remove detail lookup data instance records and replace them with business rule objects.
