NTNU Project Thesis on Discovery Technology

Product 08/01/2016 by Johnny Troset Andersen

We are proud to present the thesis “Implementation and Optimization Techniques for Business Discovery Products”, an in-depth study from the Norwegian University of Science and Technology, NTNU, co-supervised by Genus.

 

Genus Discovery is a flexible and intuitive graphical tool for exploring, analyzing and sharing data and insight with other end users, and an integral part of Genus Application Framework. With Genus Discovery, we are pushing the boundaries of modern business intelligence (BI), both in terms of usability and performance. Our customers do not need to install a separate BI product - instead, their Genus solution can be expanded to include all necessary functionality, seamlessly integrated with their existing application, thus improving usability. To make this work, a strong focus on performance is necessary. And this is exactly what the thesis at hand aims to address, namely a deep dive into optimization techniques for this type of technology.

 

The thesis is written by master student Håkon Åmdal with Professor Svein Erik Bratsberg as supervisor and our colleague and Lead Technical Architect Einar Bleikvin as co-supervisor. Professor Svein Erik Bratsberg has been a Professor at NTNU, Department of Computer and Information Science, since 2001 in distributed systems with focus on databases and search engines. Einar Bleikvin is one of the founders of Genus and has been our lead technical architect since 1996. Håkon Åmdal studies Complex Computing Systems at the Department of Computer and Information Science.

 

Håkon Åmdal will continue the research project through his Master thesis in co-operation with Genus during the first half of 2016 (you will find a draft research plan for the Master thesis in Appendix A). In parallel, Einar Bleikvin will lead our work in delivering an improved Genus Discovery to our customers as part of release 2016.1 and later releases, steadily capable of handling larger data sets in a highly optimized fashion, both with regards to memory and CPU.

 

This work is part of our ongoing co-operation with NTNU at many levels, from academic student organizations to the Department of Computer and Information Science. If you are a Master or PhD student interested in model-driven technology, please Contact Us for more information. You may also want to have a look at this depth study assignment – it will also be available during the fall of 2016.

 

Click the link below to open the thesis. If you are interested in a demonstration of Genus Discovery, please Contact Us.

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