Abstract
Big data analytics is often prohibitively costly. It is typically conducted by parallel processing with a cluster of machines, and is considered a privilege of big companies that can afford the resources. This position paper argues that big dataanalytics is accessible to small companies with constrained resources. As an evi-dence, we present BEAS, a framework for querying big relations with constrained resources, based on bounded evaluation and data-driven approximation.
Original language | English |
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Pages (from-to) | 1-7 |
Number of pages | 6 |
Journal | Data Analysis and Knowledge Discovery |
Volume | 1 |
Issue number | 9 |
DOIs | |
Publication status | Published - 27 Jul 2017 |
Keywords / Materials (for Non-textual outputs)
- Big data analytics
- Bounded evaluation
- Data-driven approximation
- Constrained resources