Data Farming: Better Data, Not Just Big Data
Loading...
Authors
Sanchez, Susan M.
Subjects
Advisors
Date of Issue
2018-12
Date
Publisher
IEEE
Language
Abstract
Data mining tools have been around for several decades, but the term “big data” has only recently captured widespread attention. Numerous success stories have been promulgated as organizations have sifted through massive volumes of data to find interesting patterns that are, in turn, transformed into actionable information. Yet a key drawback to the big data paradigm is that it relies on observational data, limiting the types of insights that can be gained. The simulation world is different. A “data farming” metaphor captures the notion of purposeful data generation from simulation models. Large-scale experiments let us grow the simulation output efficiently and effectively. We can use modern statistical and visual analytic methods to explore massive input spaces, uncover interesting features of complex simulation response surfaces, and explicitly identify cause-and-effect relationships. With this new mindset, we can achieve tremendous leaps in the breadth, depth, and timeliness of the insights yielded by simulation.
Type
Conference Paper
Description
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
15 p.
Citation
Sanchez, Susan M. "Data farming: better data, not just big data." 2018 Winter Simulation Conference (WSC). IEEE, 2018.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.