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SUMMARY
Over the recent years “big data” has became a near-ubiquitous buzzword. The term “big data” generally refers to a context where Gigabytes constitute the unit size for measuring data volumes, where Terabytes are commonly encountered, and many Web companies, scientific, and financial institutions must deal with Petabytes of information. In response to pressing practical needs a variety of systems have arisen, in an ad-hoc and improvisational manner for handling big data.
Some of these systems have led to a revival of parallel database management systems and an increased interest in so-called NoSQL data repositories. While progress in database research has lead to a deeper understanding of traditional non-distributed data models and sequential querying, progress in the area of big data computation has proved so far to be insufficient and initial models are only scarcely developed. Given the number of competing systems and their diversity, it remains unclear which system is best suited for which kind of queries. This project therefore aims to develop and study computational models for big data to provide insight into the use of existing systems and to formulate possible improvements and synergies.
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SOLUTIONS
- Developing a system which is robust against the large-scale computational complexity associated with big data
- Studying query and transformation languages for big data within the developed computational framework.
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LINK: http://www.researchportal.be/en/project/a-formal-approach-to-querying-big-data-%28UH_R-4633%29/
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