Integrating analytics with relational databases
In order to uncover insights and trends, it is an increasingly common practice for companies of all shapes and sizes to gather large quantities of data and to then analyze that data. This data can come from a multitude of different sources, ranging from data gathered about consumer behavior to data gathered from sensors. The most prevalent way of storing and managing data has traditionally been a relational database management system (RDBMS). However, there is currently a disconnect between the tools used for analysis of data and the tools used for storing that data. Instead of working directly with RDBMSes, these tools are build to work in a stand-alone fashion, and offer integration with RDBMSes as an afterthought. The focus of my PhD research is on investigating different methods of combining popular analytical tools (such as R or Python) with database management systems in an efficient and user-friendly fashion.
|Conference||2018 VLDB PhD Workshop, VLDB-PhD 2018|
Raasveldt, M. (2018). Integrating analytics with relational databases. In Proceedings of the VLDB 2018 PhD Workshop co-located with the 44th International Conference on Very Large Databases (VLDB 2018).