Analys: Bör valet få oss att ifrågasätta ”big data”?
Resultatet i det amerikanska presidentvalet kom som en chock för dem som följt de senaste opinionsmätningarna, varav de allra flesta förutspådde att Clinton skulle vinna. Det samma hände vid parlamentsvalet i Storbritannien 2015 och då landet röstade om EU medlemskap tidigare i år.
Mot bakgrund av detta frågar sig BBC nu om vi borde sluta upp med att göra opinionsundersökningar helt och hållet. Samtidigt undrar AP i en analys om vi bör förlita oss så mycket på ”big data” som vi gör i dagens samhälle om vi inte ens kan pricka rätt i opinionsundersökningar.
Störst självrannsakan råder dock bland de amerikanska opinionsinstituten, som nu jobbar med djupgående analyser om varför de hade så fel.
bakgrund
Big data
Wikipedia (en)
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term "big data" often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem."
Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on". Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, finance, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.
Data sets grow rapidly - in part because they are increasingly gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012, every day 2.5 exabytes (2.5×1018) of data is generated. One question for large enterprises is determining who should own big-data initiatives that affect the entire organization.
Relational database management systems and desktop statistics- and visualization-packages often have difficulty handling big data. The work may require "massively parallel software running on tens, hundreds, or even thousands of servers". What counts as "big data" varies depending on the capabilities of the users and their tools, and expanding capabilities make big data a moving target. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."
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