Paper Info
Title
On the path to sustainable, scalable, and energy-efficient data analytics: Challenges, promises, and future directions
Abstract
As scientific data is reaching exascale, scalable and energy efficient data analytics is quickly becoming a top notch priority. Yet, a sustainable solution to this problem is hampered by a number of technical challenges that get exacerbated with the emerging hardware and software technology trends. In this paper, we present a number of recently created “secret sauces” that promise to address some of these challenges. We discuss transformative approaches to efficient data reduction, analytics-driven query processing, scalable analytical kernels, approximate analytics, among others. We propose a number of future directions that could be pursued on the path to sustainable data analytics at scale.
Year
DOI
Venue
2012
10.1109/IGCC.2012.6322265
IGCC
Keywords
Field
DocType
analytics-driven query processing,energy-efficient data analytics,energy efficient data analytics,sustainable data analytics,sustainable solution,efficient data reduction,scalable analytical kernel,future direction,scientific data,secret sauce,approximate analytics,data mining,energy conservation,algorithm design and analysis,kernel,data reduction,data analysis,approximation algorithms,indexes,throughput
Data science,Energy conservation,Software analytics,Data analysis,Transformative learning,Computer science,Efficient energy use,Analytics,Business intelligence,Scalability
Conference
ISBN
Citations 
PageRank 
978-1-4673-2153-2
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Sriram Lakshminarasimhan118710.01
Prabhat Kumar228612.16
Wei-keng Liao3109587.98
Alok Choudhary432231.06
Vipin Kumar54331385.81
Nagiza F. Samatova686174.04