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.
|Number of pages||6|
|Journal||Data Analysis and Knowledge Discovery|
|Publication status||Published - 27 Jul 2017|
- Big data analytics
- Bounded evaluation
- Data-driven approximation
- Constrained resources