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Interposition Based Container Optimization For Data Intensive Applications, Rohan Tikmany
Interposition Based Container Optimization For Data Intensive Applications, Rohan Tikmany
College of Computing and Digital Media Dissertations
Reproducibility of applications is paramount in several scenarios such as collaborative work and software testing. Containers provide an easy way of addressing reproducibility by packaging the application's software and data dependencies into one executable unit, which can be executed multiple times in different environments. With the increased use of containers in industry as well as academia, current research has examined the provisioning and storage cost of containers and has shown that container deployments often include unnecessary software packages. Current methods to optimize the container size prune unnecessary data at the granularity of files and thus make binary decisions. We show …
Using A Data Warehouse As Part Of A General Business Process Data Analysis System, Amit Maor
Using A Data Warehouse As Part Of A General Business Process Data Analysis System, Amit Maor
CMC Senior Theses
Data analytics queries often involve aggregating over massive amounts of data, in order to detect trends in the data, make predictions about future data, and make business decisions as a result. As such, it is important that a database management system (DBMS) handling data analytics queries perform well when those queries involve massive amounts of data. A data warehouse is a DBMS which is designed specifically to handle data analytics queries.
This thesis describes the data warehouse Amazon Redshift, and how it was used to design a data analysis system for Laserfiche. Laserfiche is a software company that provides each …