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Reading: Report from the 5th Workshop on Extremely Large Databases

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Report from the 5th Workshop on Extremely Large Databases

Authors:

Jacek Becla ,

SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
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Daniel Liwei Wang,

SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
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Kian-Tat Lim

SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
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Abstract

The 5th XLDB workshop brought together scientific and industrial users, developers, and researchers of extremely large data and focused on emerging challenges in the healthcare and genomics communities, spreadsheet-based large scale analysis, and challenges in applying statistics to large scale analysis, including machine learning. Major problems discussed were the lack of scalable applications, the lack of expertise in developing solutions, the lack of respect for or attention to big data problems, data volume growth exceeding Moore's Law, poorly scaling algorithms, and poor data quality and integration. More communication between users, developers, and researchers is sorely needed. A variety of future work to help all three groups was discussed, ranging from collecting challenge problems to connecting with particular industrial or academic sectors.
DOI: http://doi.org/10.2481/dsj.012-010
How to Cite: Becla, J., Wang, D.L. & Lim, K.-T., (2012). Report from the 5th Workshop on Extremely Large Databases. Data Science Journal. 11, pp.37–45. DOI: http://doi.org/10.2481/dsj.012-010
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Published on 18 Mar 2012.
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