Search results
Results from the WOW.Com Content Network
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
The materials in the Data Science and Predictive Analytics (DSPA) textbook have been peer-reviewed in the Journal of the American Statistical Association, [5] International Statistical Institute’s ISI Review Journal, [3] and the Journal of the American Library Association. [4] Many scholarly publications reference the DSPA textbook. [6] [7]
Smart city, e-democracy, open data, intelligent environment: Digital scent technology: Diffusion Smell-O-Vision, iSmell: DNA digital data storage: Experiments Mass data storage Electronic nose: Research, limited commercialization [20] [21] Detecting spoiled food, chemical weapons, and cancer Emerging memory technologies
In more recent decades, science experiments such as CERN have produced data on similar scales to current commercial "big data". However, science experiments have tended to analyze their data using specialized custom-built high-performance computing (super-computing) clusters and grids, rather than clouds of cheap commodity computers as in the ...
Datafication is a technological trend turning many aspects of our life into data [1] [2] which is subsequently transferred into information realised as a new form of value. [3] Kenneth Cukier and Viktor Mayer-Schönberger introduced the term datafication to the broader lexicon in 2013. [ 4 ]
Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [ 10 ] Data analysis is a process for obtaining raw data , and subsequently converting it into information useful for decision-making by users. [ 1 ]
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.
Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use.