Difference between revisions of "Complex System Modeling"
Line 9: | Line 9: | ||
*[http://www.kdnuggets.com/2015/02/interview-david-kasik-boeing-data-analytics.html "Interview: David Kasik, Boeing on Data Analysis vs Data Analytics"] | *[http://www.kdnuggets.com/2015/02/interview-david-kasik-boeing-data-analytics.html "Interview: David Kasik, Boeing on Data Analysis vs Data Analytics"] | ||
+ | :Data analytics is a broader term and includes data analysis as necessary subcomponent. Analytics defines the science behind the analysis. The science means understanding the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extract, transform, and load; specific tools, techniques, and methods; and how to successfully communicate results. | ||
*[http://www.llnl.gov/casc/coopParallelism/ LLNL Cooperative Parallelism] | *[http://www.llnl.gov/casc/coopParallelism/ LLNL Cooperative Parallelism] |
Latest revision as of 07:42, 23 February 2016
Definitions from Luis Rocha, LANL
"A system comprised of a (usually large) number of (usually strongly) interacting entities, processes, or agents, the understanding of which requires the development, or the use of, new scientific tools, nonlinear models, out-of equilibrium descriptions and computer simulations." [Advances in Complex Systems Journal]
"A system that can be analyzed into many components having relatively many relations among them, so that the behavior of each component depends on the behavior of others. [Herbert Simon]"
"A system that involves numerous interacting agents whose aggregate behaviors are to be understood. Such aggregate activity is nonlinear, hence it cannot simply be derived from summation of individual components behavior." [Jerome Singer]
- Data analytics is a broader term and includes data analysis as necessary subcomponent. Analytics defines the science behind the analysis. The science means understanding the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extract, transform, and load; specific tools, techniques, and methods; and how to successfully communicate results.